Zhang, Harrison G; Ying, Gui-Shuang
2018-02-09
The aim of this study is to evaluate the current practice of statistical analysis of eye data in clinical science papers published in British Journal of Ophthalmology ( BJO ) and to determine whether the practice of statistical analysis has improved in the past two decades. All clinical science papers (n=125) published in BJO in January-June 2017 were reviewed for their statistical analysis approaches for analysing primary ocular measure. We compared our findings to the results from a previous paper that reviewed BJO papers in 1995. Of 112 papers eligible for analysis, half of the studies analysed the data at an individual level because of the nature of observation, 16 (14%) studies analysed data from one eye only, 36 (32%) studies analysed data from both eyes at ocular level, one study (1%) analysed the overall summary of ocular finding per individual and three (3%) studies used the paired comparison. Among studies with data available from both eyes, 50 (89%) of 56 papers in 2017 did not analyse data from both eyes or ignored the intereye correlation, as compared with in 60 (90%) of 67 papers in 1995 (P=0.96). Among studies that analysed data from both eyes at an ocular level, 33 (92%) of 36 studies completely ignored the intereye correlation in 2017, as compared with in 16 (89%) of 18 studies in 1995 (P=0.40). A majority of studies did not analyse the data properly when data from both eyes were available. The practice of statistical analysis did not improve in the past two decades. Collaborative efforts should be made in the vision research community to improve the practice of statistical analysis for ocular data. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Statistics for NAEG: past efforts, new results, and future plans
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gilbert, R.O.; Simpson, J.C.; Kinnison, R.R.
A brief review of Nevada Applied Ecology Group (NAEG) objectives is followed by a summary of past statistical analyses conducted by Pacific Northwest Laboratory for the NAEG. Estimates of spatial pattern of radionuclides and other statistical analyses at NS's 201, 219 and 221 are reviewed as background for new analyses presented in this paper. Suggested NAEG activities and statistical analyses needed for the projected termination date of NAEG studies in March 1986 are given.
Wu, Robert; Glen, Peter; Ramsay, Tim; Martel, Guillaume
2014-06-28
Observational studies dominate the surgical literature. Statistical adjustment is an important strategy to account for confounders in observational studies. Research has shown that published articles are often poor in statistical quality, which may jeopardize their conclusions. The Statistical Analyses and Methods in the Published Literature (SAMPL) guidelines have been published to help establish standards for statistical reporting.This study will seek to determine whether the quality of statistical adjustment and the reporting of these methods are adequate in surgical observational studies. We hypothesize that incomplete reporting will be found in all surgical observational studies, and that the quality and reporting of these methods will be of lower quality in surgical journals when compared with medical journals. Finally, this work will seek to identify predictors of high-quality reporting. This work will examine the top five general surgical and medical journals, based on a 5-year impact factor (2007-2012). All observational studies investigating an intervention related to an essential component area of general surgery (defined by the American Board of Surgery), with an exposure, outcome, and comparator, will be included in this systematic review. Essential elements related to statistical reporting and quality were extracted from the SAMPL guidelines and include domains such as intent of analysis, primary analysis, multiple comparisons, numbers and descriptive statistics, association and correlation analyses, linear regression, logistic regression, Cox proportional hazard analysis, analysis of variance, survival analysis, propensity analysis, and independent and correlated analyses. Each article will be scored as a proportion based on fulfilling criteria in relevant analyses used in the study. A logistic regression model will be built to identify variables associated with high-quality reporting. A comparison will be made between the scores of surgical observational studies published in medical versus surgical journals. Secondary outcomes will pertain to individual domains of analysis. Sensitivity analyses will be conducted. This study will explore the reporting and quality of statistical analyses in surgical observational studies published in the most referenced surgical and medical journals in 2013 and examine whether variables (including the type of journal) can predict high-quality reporting.
Jin, Zhichao; Yu, Danghui; Zhang, Luoman; Meng, Hong; Lu, Jian; Gao, Qingbin; Cao, Yang; Ma, Xiuqiang; Wu, Cheng; He, Qian; Wang, Rui; He, Jia
2010-05-25
High quality clinical research not only requires advanced professional knowledge, but also needs sound study design and correct statistical analyses. The number of clinical research articles published in Chinese medical journals has increased immensely in the past decade, but study design quality and statistical analyses have remained suboptimal. The aim of this investigation was to gather evidence on the quality of study design and statistical analyses in clinical researches conducted in China for the first decade of the new millennium. Ten (10) leading Chinese medical journals were selected and all original articles published in 1998 (N = 1,335) and 2008 (N = 1,578) were thoroughly categorized and reviewed. A well-defined and validated checklist on study design, statistical analyses, results presentation, and interpretation was used for review and evaluation. Main outcomes were the frequencies of different types of study design, error/defect proportion in design and statistical analyses, and implementation of CONSORT in randomized clinical trials. From 1998 to 2008: The error/defect proportion in statistical analyses decreased significantly ( = 12.03, p<0.001), 59.8% (545/1,335) in 1998 compared to 52.2% (664/1,578) in 2008. The overall error/defect proportion of study design also decreased ( = 21.22, p<0.001), 50.9% (680/1,335) compared to 42.40% (669/1,578). In 2008, design with randomized clinical trials remained low in single digit (3.8%, 60/1,578) with two-third showed poor results reporting (defects in 44 papers, 73.3%). Nearly half of the published studies were retrospective in nature, 49.3% (658/1,335) in 1998 compared to 48.2% (761/1,578) in 2008. Decreases in defect proportions were observed in both results presentation ( = 93.26, p<0.001), 92.7% (945/1,019) compared to 78.2% (1023/1,309) and interpretation ( = 27.26, p<0.001), 9.7% (99/1,019) compared to 4.3% (56/1,309), some serious ones persisted. Chinese medical research seems to have made significant progress regarding statistical analyses, but there remains ample room for improvement regarding study designs. Retrospective clinical studies are the most often used design, whereas randomized clinical trials are rare and often show methodological weaknesses. Urgent implementation of the CONSORT statement is imperative.
Hamel, Jean-Francois; Saulnier, Patrick; Pe, Madeline; Zikos, Efstathios; Musoro, Jammbe; Coens, Corneel; Bottomley, Andrew
2017-09-01
Over the last decades, Health-related Quality of Life (HRQoL) end-points have become an important outcome of the randomised controlled trials (RCTs). HRQoL methodology in RCTs has improved following international consensus recommendations. However, no international recommendations exist concerning the statistical analysis of such data. The aim of our study was to identify and characterise the quality of the statistical methods commonly used for analysing HRQoL data in cancer RCTs. Building on our recently published systematic review, we analysed a total of 33 published RCTs studying the HRQoL methods reported in RCTs since 1991. We focussed on the ability of the methods to deal with the three major problems commonly encountered when analysing HRQoL data: their multidimensional and longitudinal structure and the commonly high rate of missing data. All studies reported HRQoL being assessed repeatedly over time for a period ranging from 2 to 36 months. Missing data were common, with compliance rates ranging from 45% to 90%. From the 33 studies considered, 12 different statistical methods were identified. Twenty-nine studies analysed each of the questionnaire sub-dimensions without type I error adjustment. Thirteen studies repeated the HRQoL analysis at each assessment time again without type I error adjustment. Only 8 studies used methods suitable for repeated measurements. Our findings show a lack of consistency in statistical methods for analysing HRQoL data. Problems related to multiple comparisons were rarely considered leading to a high risk of false positive results. It is therefore critical that international recommendations for improving such statistical practices are developed. Copyright © 2017. Published by Elsevier Ltd.
[Statistical analysis using freely-available "EZR (Easy R)" software].
Kanda, Yoshinobu
2015-10-01
Clinicians must often perform statistical analyses for purposes such evaluating preexisting evidence and designing or executing clinical studies. R is a free software environment for statistical computing. R supports many statistical analysis functions, but does not incorporate a statistical graphical user interface (GUI). The R commander provides an easy-to-use basic-statistics GUI for R. However, the statistical function of the R commander is limited, especially in the field of biostatistics. Therefore, the author added several important statistical functions to the R commander and named it "EZR (Easy R)", which is now being distributed on the following website: http://www.jichi.ac.jp/saitama-sct/. EZR allows the application of statistical functions that are frequently used in clinical studies, such as survival analyses, including competing risk analyses and the use of time-dependent covariates and so on, by point-and-click access. In addition, by saving the script automatically created by EZR, users can learn R script writing, maintain the traceability of the analysis, and assure that the statistical process is overseen by a supervisor.
Jin, Zhichao; Yu, Danghui; Zhang, Luoman; Meng, Hong; Lu, Jian; Gao, Qingbin; Cao, Yang; Ma, Xiuqiang; Wu, Cheng; He, Qian; Wang, Rui; He, Jia
2010-01-01
Background High quality clinical research not only requires advanced professional knowledge, but also needs sound study design and correct statistical analyses. The number of clinical research articles published in Chinese medical journals has increased immensely in the past decade, but study design quality and statistical analyses have remained suboptimal. The aim of this investigation was to gather evidence on the quality of study design and statistical analyses in clinical researches conducted in China for the first decade of the new millennium. Methodology/Principal Findings Ten (10) leading Chinese medical journals were selected and all original articles published in 1998 (N = 1,335) and 2008 (N = 1,578) were thoroughly categorized and reviewed. A well-defined and validated checklist on study design, statistical analyses, results presentation, and interpretation was used for review and evaluation. Main outcomes were the frequencies of different types of study design, error/defect proportion in design and statistical analyses, and implementation of CONSORT in randomized clinical trials. From 1998 to 2008: The error/defect proportion in statistical analyses decreased significantly ( = 12.03, p<0.001), 59.8% (545/1,335) in 1998 compared to 52.2% (664/1,578) in 2008. The overall error/defect proportion of study design also decreased ( = 21.22, p<0.001), 50.9% (680/1,335) compared to 42.40% (669/1,578). In 2008, design with randomized clinical trials remained low in single digit (3.8%, 60/1,578) with two-third showed poor results reporting (defects in 44 papers, 73.3%). Nearly half of the published studies were retrospective in nature, 49.3% (658/1,335) in 1998 compared to 48.2% (761/1,578) in 2008. Decreases in defect proportions were observed in both results presentation ( = 93.26, p<0.001), 92.7% (945/1,019) compared to 78.2% (1023/1,309) and interpretation ( = 27.26, p<0.001), 9.7% (99/1,019) compared to 4.3% (56/1,309), some serious ones persisted. Conclusions/Significance Chinese medical research seems to have made significant progress regarding statistical analyses, but there remains ample room for improvement regarding study designs. Retrospective clinical studies are the most often used design, whereas randomized clinical trials are rare and often show methodological weaknesses. Urgent implementation of the CONSORT statement is imperative. PMID:20520824
Secondary Analysis of National Longitudinal Transition Study 2 Data
ERIC Educational Resources Information Center
Hicks, Tyler A.; Knollman, Greg A.
2015-01-01
This review examines published secondary analyses of National Longitudinal Transition Study 2 (NLTS2) data, with a primary focus upon statistical objectives, paradigms, inferences, and methods. Its primary purpose was to determine which statistical techniques have been common in secondary analyses of NLTS2 data. The review begins with an…
Papageorgiou, Spyridon N; Kloukos, Dimitrios; Petridis, Haralampos; Pandis, Nikolaos
2015-10-01
To assess the hypothesis that there is excessive reporting of statistically significant studies published in prosthodontic and implantology journals, which could indicate selective publication. The last 30 issues of 9 journals in prosthodontics and implant dentistry were hand-searched for articles with statistical analyses. The percentages of significant and non-significant results were tabulated by parameter of interest. Univariable/multivariable logistic regression analyses were applied to identify possible predictors of reporting statistically significance findings. The results of this study were compared with similar studies in dentistry with random-effects meta-analyses. From the 2323 included studies 71% of them reported statistically significant results, with the significant results ranging from 47% to 86%. Multivariable modeling identified that geographical area and involvement of statistician were predictors of statistically significant results. Compared to interventional studies, the odds that in vitro and observational studies would report statistically significant results was increased by 1.20 times (OR: 2.20, 95% CI: 1.66-2.92) and 0.35 times (OR: 1.35, 95% CI: 1.05-1.73), respectively. The probability of statistically significant results from randomized controlled trials was significantly lower compared to various study designs (difference: 30%, 95% CI: 11-49%). Likewise the probability of statistically significant results in prosthodontics and implant dentistry was lower compared to other dental specialties, but this result did not reach statistical significant (P>0.05). The majority of studies identified in the fields of prosthodontics and implant dentistry presented statistically significant results. The same trend existed in publications of other specialties in dentistry. Copyright © 2015 Elsevier Ltd. All rights reserved.
A d-statistic for single-case designs that is equivalent to the usual between-groups d-statistic.
Shadish, William R; Hedges, Larry V; Pustejovsky, James E; Boyajian, Jonathan G; Sullivan, Kristynn J; Andrade, Alma; Barrientos, Jeannette L
2014-01-01
We describe a standardised mean difference statistic (d) for single-case designs that is equivalent to the usual d in between-groups experiments. We show how it can be used to summarise treatment effects over cases within a study, to do power analyses in planning new studies and grant proposals, and to meta-analyse effects across studies of the same question. We discuss limitations of this d-statistic, and possible remedies to them. Even so, this d-statistic is better founded statistically than other effect size measures for single-case design, and unlike many general linear model approaches such as multilevel modelling or generalised additive models, it produces a standardised effect size that can be integrated over studies with different outcome measures. SPSS macros for both effect size computation and power analysis are available.
Inferential Statistics in "Language Teaching Research": A Review and Ways Forward
ERIC Educational Resources Information Center
Lindstromberg, Seth
2016-01-01
This article reviews all (quasi)experimental studies appearing in the first 19 volumes (1997-2015) of "Language Teaching Research" (LTR). Specifically, it provides an overview of how statistical analyses were conducted in these studies and of how the analyses were reported. The overall conclusion is that there has been a tight adherence…
Extreme between-study homogeneity in meta-analyses could offer useful insights.
Ioannidis, John P A; Trikalinos, Thomas A; Zintzaras, Elias
2006-10-01
Meta-analyses are routinely evaluated for the presence of large between-study heterogeneity. We examined whether it is also important to probe whether there is extreme between-study homogeneity. We used heterogeneity tests with left-sided statistical significance for inference and developed a Monte Carlo simulation test for testing extreme homogeneity in risk ratios across studies, using the empiric distribution of the summary risk ratio and heterogeneity statistic. A left-sided P=0.01 threshold was set for claiming extreme homogeneity to minimize type I error. Among 11,803 meta-analyses with binary contrasts from the Cochrane Library, 143 (1.21%) had left-sided P-value <0.01 for the asymptotic Q statistic and 1,004 (8.50%) had left-sided P-value <0.10. The frequency of extreme between-study homogeneity did not depend on the number of studies in the meta-analyses. We identified examples where extreme between-study homogeneity (left-sided P-value <0.01) could result from various possibilities beyond chance. These included inappropriate statistical inference (asymptotic vs. Monte Carlo), use of a specific effect metric, correlated data or stratification using strong predictors of outcome, and biases and potential fraud. Extreme between-study homogeneity may provide useful insights about a meta-analysis and its constituent studies.
Huvane, Jacqueline; Komarow, Lauren; Hill, Carol; Tran, Thuy Tien T.; Pereira, Carol; Rosenkranz, Susan L.; Finnemeyer, Matt; Earley, Michelle; Jiang, Hongyu (Jeanne); Wang, Rui; Lok, Judith
2017-01-01
Abstract The Statistical and Data Management Center (SDMC) provides the Antibacterial Resistance Leadership Group (ARLG) with statistical and data management expertise to advance the ARLG research agenda. The SDMC is active at all stages of a study, including design; data collection and monitoring; data analyses and archival; and publication of study results. The SDMC enhances the scientific integrity of ARLG studies through the development and implementation of innovative and practical statistical methodologies and by educating research colleagues regarding the application of clinical trial fundamentals. This article summarizes the challenges and roles, as well as the innovative contributions in the design, monitoring, and analyses of clinical trials and diagnostic studies, of the ARLG SDMC. PMID:28350899
Sequi, Marco; Campi, Rita; Clavenna, Antonio; Bonati, Maurizio
2013-03-01
To evaluate the quality of data reporting and statistical methods performed in drug utilization studies in the pediatric population. Drug utilization studies evaluating all drug prescriptions to children and adolescents published between January 1994 and December 2011 were retrieved and analyzed. For each study, information on measures of exposure/consumption, the covariates considered, descriptive and inferential analyses, statistical tests, and methods of data reporting was extracted. An overall quality score was created for each study using a 12-item checklist that took into account the presence of outcome measures, covariates of measures, descriptive measures, statistical tests, and graphical representation. A total of 22 studies were reviewed and analyzed. Of these, 20 studies reported at least one descriptive measure. The mean was the most commonly used measure (18 studies), but only five of these also reported the standard deviation. Statistical analyses were performed in 12 studies, with the chi-square test being the most commonly performed test. Graphs were presented in 14 papers. Sixteen papers reported the number of drug prescriptions and/or packages, and ten reported the prevalence of the drug prescription. The mean quality score was 8 (median 9). Only seven of the 22 studies received a score of ≥10, while four studies received a score of <6. Our findings document that only a few of the studies reviewed applied statistical methods and reported data in a satisfactory manner. We therefore conclude that the methodology of drug utilization studies needs to be improved.
[Clinical research=design*measurements*statistical analyses].
Furukawa, Toshiaki
2012-06-01
A clinical study must address true endpoints that matter for the patients and the doctors. A good clinical study starts with a good clinical question. Formulating a clinical question in the form of PECO can sharpen one's original question. In order to perform a good clinical study one must have a knowledge of study design, measurements and statistical analyses: The first is taught by epidemiology, the second by psychometrics and the third by biostatistics.
Post Hoc Analyses of ApoE Genotype-Defined Subgroups in Clinical Trials.
Kennedy, Richard E; Cutter, Gary R; Wang, Guoqiao; Schneider, Lon S
2016-01-01
Many post hoc analyses of clinical trials in Alzheimer's disease (AD) and mild cognitive impairment (MCI) are in small Phase 2 trials. Subject heterogeneity may lead to statistically significant post hoc results that cannot be replicated in larger follow-up studies. We investigated the extent of this problem using simulation studies mimicking current trial methods with post hoc analyses based on ApoE4 carrier status. We used a meta-database of 24 studies, including 3,574 subjects with mild AD and 1,171 subjects with MCI/prodromal AD, to simulate clinical trial scenarios. Post hoc analyses examined if rates of progression on the Alzheimer's Disease Assessment Scale-cognitive (ADAS-cog) differed between ApoE4 carriers and non-carriers. Across studies, ApoE4 carriers were younger and had lower baseline scores, greater rates of progression, and greater variability on the ADAS-cog. Up to 18% of post hoc analyses for 18-month trials in AD showed greater rates of progression for ApoE4 non-carriers that were statistically significant but unlikely to be confirmed in follow-up studies. The frequency of erroneous conclusions dropped below 3% with trials of 100 subjects per arm. In MCI, rates of statistically significant differences with greater progression in ApoE4 non-carriers remained below 3% unless sample sizes were below 25 subjects per arm. Statistically significant differences for ApoE4 in post hoc analyses often reflect heterogeneity among small samples rather than true differential effect among ApoE4 subtypes. Such analyses must be viewed cautiously. ApoE genotype should be incorporated into the design stage to minimize erroneous conclusions.
Use of Statistical Analyses in the Ophthalmic Literature
Lisboa, Renato; Meira-Freitas, Daniel; Tatham, Andrew J.; Marvasti, Amir H.; Sharpsten, Lucie; Medeiros, Felipe A.
2014-01-01
Purpose To identify the most commonly used statistical analyses in the ophthalmic literature and to determine the likely gain in comprehension of the literature that readers could expect if they were to sequentially add knowledge of more advanced techniques to their statistical repertoire. Design Cross-sectional study Methods All articles published from January 2012 to December 2012 in Ophthalmology, American Journal of Ophthalmology and Archives of Ophthalmology were reviewed. A total of 780 peer-reviewed articles were included. Two reviewers examined each article and assigned categories to each one depending on the type of statistical analyses used. Discrepancies between reviewers were resolved by consensus. Main Outcome Measures Total number and percentage of articles containing each category of statistical analysis were obtained. Additionally we estimated the accumulated number and percentage of articles that a reader would be expected to be able to interpret depending on their statistical repertoire. Results Readers with little or no statistical knowledge would be expected to be able to interpret the statistical methods presented in only 20.8% of articles. In order to understand more than half (51.4%) of the articles published, readers were expected to be familiar with at least 15 different statistical methods. Knowledge of 21 categories of statistical methods was necessary to comprehend 70.9% of articles, while knowledge of more than 29 categories was necessary to comprehend more than 90% of articles. Articles in retina and glaucoma subspecialties showed a tendency for using more complex analysis when compared to cornea. Conclusions Readers of clinical journals in ophthalmology need to have substantial knowledge of statistical methodology to understand the results of published studies in the literature. The frequency of use of complex statistical analyses also indicates that those involved in the editorial peer-review process must have sound statistical knowledge in order to critically appraise articles submitted for publication. The results of this study could provide guidance to direct the statistical learning of clinical ophthalmologists, researchers and educators involved in the design of courses for residents and medical students. PMID:24612977
Dwan, Kerry; Altman, Douglas G.; Clarke, Mike; Gamble, Carrol; Higgins, Julian P. T.; Sterne, Jonathan A. C.; Williamson, Paula R.; Kirkham, Jamie J.
2014-01-01
Background Most publications about selective reporting in clinical trials have focussed on outcomes. However, selective reporting of analyses for a given outcome may also affect the validity of findings. If analyses are selected on the basis of the results, reporting bias may occur. The aims of this study were to review and summarise the evidence from empirical cohort studies that assessed discrepant or selective reporting of analyses in randomised controlled trials (RCTs). Methods and Findings A systematic review was conducted and included cohort studies that assessed any aspect of the reporting of analyses of RCTs by comparing different trial documents, e.g., protocol compared to trial report, or different sections within a trial publication. The Cochrane Methodology Register, Medline (Ovid), PsycInfo (Ovid), and PubMed were searched on 5 February 2014. Two authors independently selected studies, performed data extraction, and assessed the methodological quality of the eligible studies. Twenty-two studies (containing 3,140 RCTs) published between 2000 and 2013 were included. Twenty-two studies reported on discrepancies between information given in different sources. Discrepancies were found in statistical analyses (eight studies), composite outcomes (one study), the handling of missing data (three studies), unadjusted versus adjusted analyses (three studies), handling of continuous data (three studies), and subgroup analyses (12 studies). Discrepancy rates varied, ranging from 7% (3/42) to 88% (7/8) in statistical analyses, 46% (36/79) to 82% (23/28) in adjusted versus unadjusted analyses, and 61% (11/18) to 100% (25/25) in subgroup analyses. This review is limited in that none of the included studies investigated the evidence for bias resulting from selective reporting of analyses. It was not possible to combine studies to provide overall summary estimates, and so the results of studies are discussed narratively. Conclusions Discrepancies in analyses between publications and other study documentation were common, but reasons for these discrepancies were not discussed in the trial reports. To ensure transparency, protocols and statistical analysis plans need to be published, and investigators should adhere to these or explain discrepancies. Please see later in the article for the Editors' Summary PMID:24959719
Gaskin, Cadeyrn J; Happell, Brenda
2014-05-01
To (a) assess the statistical power of nursing research to detect small, medium, and large effect sizes; (b) estimate the experiment-wise Type I error rate in these studies; and (c) assess the extent to which (i) a priori power analyses, (ii) effect sizes (and interpretations thereof), and (iii) confidence intervals were reported. Statistical review. Papers published in the 2011 volumes of the 10 highest ranked nursing journals, based on their 5-year impact factors. Papers were assessed for statistical power, control of experiment-wise Type I error, reporting of a priori power analyses, reporting and interpretation of effect sizes, and reporting of confidence intervals. The analyses were based on 333 papers, from which 10,337 inferential statistics were identified. The median power to detect small, medium, and large effect sizes was .40 (interquartile range [IQR]=.24-.71), .98 (IQR=.85-1.00), and 1.00 (IQR=1.00-1.00), respectively. The median experiment-wise Type I error rate was .54 (IQR=.26-.80). A priori power analyses were reported in 28% of papers. Effect sizes were routinely reported for Spearman's rank correlations (100% of papers in which this test was used), Poisson regressions (100%), odds ratios (100%), Kendall's tau correlations (100%), Pearson's correlations (99%), logistic regressions (98%), structural equation modelling/confirmatory factor analyses/path analyses (97%), and linear regressions (83%), but were reported less often for two-proportion z tests (50%), analyses of variance/analyses of covariance/multivariate analyses of variance (18%), t tests (8%), Wilcoxon's tests (8%), Chi-squared tests (8%), and Fisher's exact tests (7%), and not reported for sign tests, Friedman's tests, McNemar's tests, multi-level models, and Kruskal-Wallis tests. Effect sizes were infrequently interpreted. Confidence intervals were reported in 28% of papers. The use, reporting, and interpretation of inferential statistics in nursing research need substantial improvement. Most importantly, researchers should abandon the misleading practice of interpreting the results from inferential tests based solely on whether they are statistically significant (or not) and, instead, focus on reporting and interpreting effect sizes, confidence intervals, and significance levels. Nursing researchers also need to conduct and report a priori power analyses, and to address the issue of Type I experiment-wise error inflation in their studies. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.
Tuuli, Methodius G; Odibo, Anthony O
2011-08-01
The objective of this article is to discuss the rationale for common statistical tests used for the analysis and interpretation of prenatal diagnostic imaging studies. Examples from the literature are used to illustrate descriptive and inferential statistics. The uses and limitations of linear and logistic regression analyses are discussed in detail.
Rao, Goutham; Lopez-Jimenez, Francisco; Boyd, Jack; D'Amico, Frank; Durant, Nefertiti H; Hlatky, Mark A; Howard, George; Kirley, Katherine; Masi, Christopher; Powell-Wiley, Tiffany M; Solomonides, Anthony E; West, Colin P; Wessel, Jennifer
2017-09-05
Meta-analyses are becoming increasingly popular, especially in the fields of cardiovascular disease prevention and treatment. They are often considered to be a reliable source of evidence for making healthcare decisions. Unfortunately, problems among meta-analyses such as the misapplication and misinterpretation of statistical methods and tests are long-standing and widespread. The purposes of this statement are to review key steps in the development of a meta-analysis and to provide recommendations that will be useful for carrying out meta-analyses and for readers and journal editors, who must interpret the findings and gauge methodological quality. To make the statement practical and accessible, detailed descriptions of statistical methods have been omitted. Based on a survey of cardiovascular meta-analyses, published literature on methodology, expert consultation, and consensus among the writing group, key recommendations are provided. Recommendations reinforce several current practices, including protocol registration; comprehensive search strategies; methods for data extraction and abstraction; methods for identifying, measuring, and dealing with heterogeneity; and statistical methods for pooling results. Other practices should be discontinued, including the use of levels of evidence and evidence hierarchies to gauge the value and impact of different study designs (including meta-analyses) and the use of structured tools to assess the quality of studies to be included in a meta-analysis. We also recommend choosing a pooling model for conventional meta-analyses (fixed effect or random effects) on the basis of clinical and methodological similarities among studies to be included, rather than the results of a test for statistical heterogeneity. © 2017 American Heart Association, Inc.
Nonindependence and sensitivity analyses in ecological and evolutionary meta-analyses.
Noble, Daniel W A; Lagisz, Malgorzata; O'dea, Rose E; Nakagawa, Shinichi
2017-05-01
Meta-analysis is an important tool for synthesizing research on a variety of topics in ecology and evolution, including molecular ecology, but can be susceptible to nonindependence. Nonindependence can affect two major interrelated components of a meta-analysis: (i) the calculation of effect size statistics and (ii) the estimation of overall meta-analytic estimates and their uncertainty. While some solutions to nonindependence exist at the statistical analysis stages, there is little advice on what to do when complex analyses are not possible, or when studies with nonindependent experimental designs exist in the data. Here we argue that exploring the effects of procedural decisions in a meta-analysis (e.g. inclusion of different quality data, choice of effect size) and statistical assumptions (e.g. assuming no phylogenetic covariance) using sensitivity analyses are extremely important in assessing the impact of nonindependence. Sensitivity analyses can provide greater confidence in results and highlight important limitations of empirical work (e.g. impact of study design on overall effects). Despite their importance, sensitivity analyses are seldom applied to problems of nonindependence. To encourage better practice for dealing with nonindependence in meta-analytic studies, we present accessible examples demonstrating the impact that ignoring nonindependence can have on meta-analytic estimates. We also provide pragmatic solutions for dealing with nonindependent study designs, and for analysing dependent effect sizes. Additionally, we offer reporting guidelines that will facilitate disclosure of the sources of nonindependence in meta-analyses, leading to greater transparency and more robust conclusions. © 2017 John Wiley & Sons Ltd.
Dissecting the genetics of complex traits using summary association statistics.
Pasaniuc, Bogdan; Price, Alkes L
2017-02-01
During the past decade, genome-wide association studies (GWAS) have been used to successfully identify tens of thousands of genetic variants associated with complex traits and diseases. These studies have produced extensive repositories of genetic variation and trait measurements across large numbers of individuals, providing tremendous opportunities for further analyses. However, privacy concerns and other logistical considerations often limit access to individual-level genetic data, motivating the development of methods that analyse summary association statistics. Here, we review recent progress on statistical methods that leverage summary association data to gain insights into the genetic basis of complex traits and diseases.
Statistical innovations in diagnostic device evaluation.
Yu, Tinghui; Li, Qin; Gray, Gerry; Yue, Lilly Q
2016-01-01
Due to rapid technological development, innovations in diagnostic devices are proceeding at an extremely fast pace. Accordingly, the needs for adopting innovative statistical methods have emerged in the evaluation of diagnostic devices. Statisticians in the Center for Devices and Radiological Health at the Food and Drug Administration have provided leadership in implementing statistical innovations. The innovations discussed in this article include: the adoption of bootstrap and Jackknife methods, the implementation of appropriate multiple reader multiple case study design, the application of robustness analyses for missing data, and the development of study designs and data analyses for companion diagnostics.
ERIC Educational Resources Information Center
Merrill, Ray M.; Chatterley, Amanda; Shields, Eric C.
2005-01-01
This study explored the effectiveness of selected statistical measures at motivating or maintaining regular exercise among college students. The study also considered whether ease in understanding these statistical measures was associated with perceived effectiveness at motivating or maintaining regular exercise. Analyses were based on a…
Chung, Sang M; Lee, David J; Hand, Austin; Young, Philip; Vaidyanathan, Jayabharathi; Sahajwalla, Chandrahas
2015-12-01
The study evaluated whether the renal function decline rate per year with age in adults varies based on two primary statistical analyses: cross-section (CS), using one observation per subject, and longitudinal (LT), using multiple observations per subject over time. A total of 16628 records (3946 subjects; age range 30-92 years) of creatinine clearance and relevant demographic data were used. On average, four samples per subject were collected for up to 2364 days (mean: 793 days). A simple linear regression and random coefficient models were selected for CS and LT analyses, respectively. The renal function decline rates per year were 1.33 and 0.95 ml/min/year for CS and LT analyses, respectively, and were slower when the repeated individual measurements were considered. The study confirms that rates are different based on statistical analyses, and that a statistically robust longitudinal model with a proper sampling design provides reliable individual as well as population estimates of the renal function decline rates per year with age in adults. In conclusion, our findings indicated that one should be cautious in interpreting the renal function decline rate with aging information because its estimation was highly dependent on the statistical analyses. From our analyses, a population longitudinal analysis (e.g. random coefficient model) is recommended if individualization is critical, such as a dose adjustment based on renal function during a chronic therapy. Copyright © 2015 John Wiley & Sons, Ltd.
Pike, Katie; Nash, Rachel L; Murphy, Gavin J; Reeves, Barnaby C; Rogers, Chris A
2015-02-22
The Transfusion Indication Threshold Reduction (TITRe2) trial is the largest randomized controlled trial to date to compare red blood cell transfusion strategies following cardiac surgery. This update presents the statistical analysis plan, detailing how the study will be analyzed and presented. The statistical analysis plan has been written following recommendations from the International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use, prior to database lock and the final analysis of trial data. Outlined analyses are in line with the Consolidated Standards of Reporting Trials (CONSORT). The study aims to randomize 2000 patients from 17 UK centres. Patients are randomized to either a restrictive (transfuse if haemoglobin concentration <7.5 g/dl) or liberal (transfuse if haemoglobin concentration <9 g/dl) transfusion strategy. The primary outcome is a binary composite outcome of any serious infectious or ischaemic event in the first 3 months following randomization. The statistical analysis plan details how non-adherence with the intervention, withdrawals from the study, and the study population will be derived and dealt with in the analysis. The planned analyses of the trial primary and secondary outcome measures are described in detail, including approaches taken to deal with multiple testing, model assumptions not being met and missing data. Details of planned subgroup and sensitivity analyses and pre-specified ancillary analyses are given, along with potential issues that have been identified with such analyses and possible approaches to overcome such issues. ISRCTN70923932 .
Research Design and Statistical Methods in Indian Medical Journals: A Retrospective Survey
Hassan, Shabbeer; Yellur, Rajashree; Subramani, Pooventhan; Adiga, Poornima; Gokhale, Manoj; Iyer, Manasa S.; Mayya, Shreemathi S.
2015-01-01
Good quality medical research generally requires not only an expertise in the chosen medical field of interest but also a sound knowledge of statistical methodology. The number of medical research articles which have been published in Indian medical journals has increased quite substantially in the past decade. The aim of this study was to collate all evidence on study design quality and statistical analyses used in selected leading Indian medical journals. Ten (10) leading Indian medical journals were selected based on impact factors and all original research articles published in 2003 (N = 588) and 2013 (N = 774) were categorized and reviewed. A validated checklist on study design, statistical analyses, results presentation, and interpretation was used for review and evaluation of the articles. Main outcomes considered in the present study were – study design types and their frequencies, error/defects proportion in study design, statistical analyses, and implementation of CONSORT checklist in RCT (randomized clinical trials). From 2003 to 2013: The proportion of erroneous statistical analyses did not decrease (χ2=0.592, Φ=0.027, p=0.4418), 25% (80/320) in 2003 compared to 22.6% (111/490) in 2013. Compared with 2003, significant improvement was seen in 2013; the proportion of papers using statistical tests increased significantly (χ2=26.96, Φ=0.16, p<0.0001) from 42.5% (250/588) to 56.7 % (439/774). The overall proportion of errors in study design decreased significantly (χ2=16.783, Φ=0.12 p<0.0001), 41.3% (243/588) compared to 30.6% (237/774). In 2013, randomized clinical trials designs has remained very low (7.3%, 43/588) with majority showing some errors (41 papers, 95.3%). Majority of the published studies were retrospective in nature both in 2003 [79.1% (465/588)] and in 2013 [78.2% (605/774)]. Major decreases in error proportions were observed in both results presentation (χ2=24.477, Φ=0.17, p<0.0001), 82.2% (263/320) compared to 66.3% (325/490) and interpretation (χ2=25.616, Φ=0.173, p<0.0001), 32.5% (104/320) compared to 17.1% (84/490), though some serious ones were still present. Indian medical research seems to have made no major progress regarding using correct statistical analyses, but error/defects in study designs have decreased significantly. Randomized clinical trials are quite rarely published and have high proportion of methodological problems. PMID:25856194
Research design and statistical methods in Indian medical journals: a retrospective survey.
Hassan, Shabbeer; Yellur, Rajashree; Subramani, Pooventhan; Adiga, Poornima; Gokhale, Manoj; Iyer, Manasa S; Mayya, Shreemathi S
2015-01-01
Good quality medical research generally requires not only an expertise in the chosen medical field of interest but also a sound knowledge of statistical methodology. The number of medical research articles which have been published in Indian medical journals has increased quite substantially in the past decade. The aim of this study was to collate all evidence on study design quality and statistical analyses used in selected leading Indian medical journals. Ten (10) leading Indian medical journals were selected based on impact factors and all original research articles published in 2003 (N = 588) and 2013 (N = 774) were categorized and reviewed. A validated checklist on study design, statistical analyses, results presentation, and interpretation was used for review and evaluation of the articles. Main outcomes considered in the present study were - study design types and their frequencies, error/defects proportion in study design, statistical analyses, and implementation of CONSORT checklist in RCT (randomized clinical trials). From 2003 to 2013: The proportion of erroneous statistical analyses did not decrease (χ2=0.592, Φ=0.027, p=0.4418), 25% (80/320) in 2003 compared to 22.6% (111/490) in 2013. Compared with 2003, significant improvement was seen in 2013; the proportion of papers using statistical tests increased significantly (χ2=26.96, Φ=0.16, p<0.0001) from 42.5% (250/588) to 56.7 % (439/774). The overall proportion of errors in study design decreased significantly (χ2=16.783, Φ=0.12 p<0.0001), 41.3% (243/588) compared to 30.6% (237/774). In 2013, randomized clinical trials designs has remained very low (7.3%, 43/588) with majority showing some errors (41 papers, 95.3%). Majority of the published studies were retrospective in nature both in 2003 [79.1% (465/588)] and in 2013 [78.2% (605/774)]. Major decreases in error proportions were observed in both results presentation (χ2=24.477, Φ=0.17, p<0.0001), 82.2% (263/320) compared to 66.3% (325/490) and interpretation (χ2=25.616, Φ=0.173, p<0.0001), 32.5% (104/320) compared to 17.1% (84/490), though some serious ones were still present. Indian medical research seems to have made no major progress regarding using correct statistical analyses, but error/defects in study designs have decreased significantly. Randomized clinical trials are quite rarely published and have high proportion of methodological problems.
Accounting for Multiple Births in Neonatal and Perinatal Trials: Systematic Review and Case Study
Hibbs, Anna Maria; Black, Dennis; Palermo, Lisa; Cnaan, Avital; Luan, Xianqun; Truog, William E; Walsh, Michele C; Ballard, Roberta A
2010-01-01
Objectives To determine the prevalence in the neonatal literature of statistical approaches accounting for the unique clustering patterns of multiple births. To explore the sensitivity of an actual trial to several analytic approaches to multiples. Methods A systematic review of recent perinatal trials assessed the prevalence of studies accounting for clustering of multiples. The NO CLD trial served as a case study of the sensitivity of the outcome to several statistical strategies. We calculated odds ratios using non-clustered (logistic regression) and clustered (generalized estimating equations, multiple outputation) analyses. Results In the systematic review, most studies did not describe the randomization of twins and did not account for clustering. Of those studies that did, exclusion of multiples and generalized estimating equations were the most common strategies. The NO CLD study included 84 infants with a sibling enrolled in the study. Multiples were more likely than singletons to be white and were born to older mothers (p<0.01). Analyses that accounted for clustering were statistically significant; analyses assuming independence were not. Conclusions The statistical approach to multiples can influence the odds ratio and width of confidence intervals, thereby affecting the interpretation of a study outcome. A minority of perinatal studies address this issue. PMID:19969305
Accounting for multiple births in neonatal and perinatal trials: systematic review and case study.
Hibbs, Anna Maria; Black, Dennis; Palermo, Lisa; Cnaan, Avital; Luan, Xianqun; Truog, William E; Walsh, Michele C; Ballard, Roberta A
2010-02-01
To determine the prevalence in the neonatal literature of statistical approaches accounting for the unique clustering patterns of multiple births and to explore the sensitivity of an actual trial to several analytic approaches to multiples. A systematic review of recent perinatal trials assessed the prevalence of studies accounting for clustering of multiples. The Nitric Oxide to Prevent Chronic Lung Disease (NO CLD) trial served as a case study of the sensitivity of the outcome to several statistical strategies. We calculated odds ratios using nonclustered (logistic regression) and clustered (generalized estimating equations, multiple outputation) analyses. In the systematic review, most studies did not describe the random assignment of twins and did not account for clustering. Of those studies that did, exclusion of multiples and generalized estimating equations were the most common strategies. The NO CLD study included 84 infants with a sibling enrolled in the study. Multiples were more likely than singletons to be white and were born to older mothers (P < .01). Analyses that accounted for clustering were statistically significant; analyses assuming independence were not. The statistical approach to multiples can influence the odds ratio and width of confidence intervals, thereby affecting the interpretation of a study outcome. A minority of perinatal studies address this issue. Copyright 2010 Mosby, Inc. All rights reserved.
2014-01-01
Objective To offer a practical demonstration of receiver operating characteristic (ROC) analyses, diagnostic efficiency statistics, and their application to clinical decision making using a popular parent checklist to assess for potential mood disorder. Method Secondary analyses of data from 589 families seeking outpatient mental health services, completing the Child Behavior Checklist and semi-structured diagnostic interviews. Results Internalizing Problems raw scores discriminated mood disorders significantly better than did age- and gender-normed T scores, or an Affective Problems score. Internalizing scores <8 had a diagnostic likelihood ratio <0.3, and scores >30 had a diagnostic likelihood ratio of 7.4. Conclusions This study illustrates a series of steps in defining a clinical problem, operationalizing it, selecting a valid study design, and using ROC analyses to generate statistics that support clinical decisions. The ROC framework offers important advantages for clinical interpretation. Appendices include sample scripts using SPSS and R to check assumptions and conduct ROC analyses. PMID:23965298
Youngstrom, Eric A
2014-03-01
To offer a practical demonstration of receiver operating characteristic (ROC) analyses, diagnostic efficiency statistics, and their application to clinical decision making using a popular parent checklist to assess for potential mood disorder. Secondary analyses of data from 589 families seeking outpatient mental health services, completing the Child Behavior Checklist and semi-structured diagnostic interviews. Internalizing Problems raw scores discriminated mood disorders significantly better than did age- and gender-normed T scores, or an Affective Problems score. Internalizing scores <8 had a diagnostic likelihood ratio <0.3, and scores >30 had a diagnostic likelihood ratio of 7.4. This study illustrates a series of steps in defining a clinical problem, operationalizing it, selecting a valid study design, and using ROC analyses to generate statistics that support clinical decisions. The ROC framework offers important advantages for clinical interpretation. Appendices include sample scripts using SPSS and R to check assumptions and conduct ROC analyses.
Huvane, Jacqueline; Komarow, Lauren; Hill, Carol; Tran, Thuy Tien T; Pereira, Carol; Rosenkranz, Susan L; Finnemeyer, Matt; Earley, Michelle; Jiang, Hongyu Jeanne; Wang, Rui; Lok, Judith; Evans, Scott R
2017-03-15
The Statistical and Data Management Center (SDMC) provides the Antibacterial Resistance Leadership Group (ARLG) with statistical and data management expertise to advance the ARLG research agenda. The SDMC is active at all stages of a study, including design; data collection and monitoring; data analyses and archival; and publication of study results. The SDMC enhances the scientific integrity of ARLG studies through the development and implementation of innovative and practical statistical methodologies and by educating research colleagues regarding the application of clinical trial fundamentals. This article summarizes the challenges and roles, as well as the innovative contributions in the design, monitoring, and analyses of clinical trials and diagnostic studies, of the ARLG SDMC. © The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.
Becker, Betsy Jane; Aloe, Ariel M; Duvendack, Maren; Stanley, T D; Valentine, Jeffrey C; Fretheim, Atle; Tugwell, Peter
2017-09-01
To outline issues of importance to analytic approaches to the synthesis of quasi-experiments (QEs) and to provide a statistical model for use in analysis. We drew on studies of statistics, epidemiology, and social-science methodology to outline methods for synthesis of QE studies. The design and conduct of QEs, effect sizes from QEs, and moderator variables for the analysis of those effect sizes were discussed. Biases, confounding, design complexities, and comparisons across designs offer serious challenges to syntheses of QEs. Key components of meta-analyses of QEs were identified, including the aspects of QE study design to be coded and analyzed. Of utmost importance are the design and statistical controls implemented in the QEs. Such controls and any potential sources of bias and confounding must be modeled in analyses, along with aspects of the interventions and populations studied. Because of such controls, effect sizes from QEs are more complex than those from randomized experiments. A statistical meta-regression model that incorporates important features of the QEs under review was presented. Meta-analyses of QEs provide particular challenges, but thorough coding of intervention characteristics and study methods, along with careful analysis, should allow for sound inferences. Copyright © 2017 Elsevier Inc. All rights reserved.
Huh, Iksoo; Wu, Xin; Park, Taesung; Yi, Soojin V
2017-07-21
DNA methylation is one of the most extensively studied epigenetic modifications of genomic DNA. In recent years, sequencing of bisulfite-converted DNA, particularly via next-generation sequencing technologies, has become a widely popular method to study DNA methylation. This method can be readily applied to a variety of species, dramatically expanding the scope of DNA methylation studies beyond the traditionally studied human and mouse systems. In parallel to the increasing wealth of genomic methylation profiles, many statistical tools have been developed to detect differentially methylated loci (DMLs) or differentially methylated regions (DMRs) between biological conditions. We discuss and summarize several key properties of currently available tools to detect DMLs and DMRs from sequencing of bisulfite-converted DNA. However, the majority of the statistical tools developed for DML/DMR analyses have been validated using only mammalian data sets, and less priority has been placed on the analyses of invertebrate or plant DNA methylation data. We demonstrate that genomic methylation profiles of non-mammalian species are often highly distinct from those of mammalian species using examples of honey bees and humans. We then discuss how such differences in data properties may affect statistical analyses. Based on these differences, we provide three specific recommendations to improve the power and accuracy of DML and DMR analyses of invertebrate data when using currently available statistical tools. These considerations should facilitate systematic and robust analyses of DNA methylation from diverse species, thus advancing our understanding of DNA methylation. © The Author 2017. Published by Oxford University Press.
Power-up: A Reanalysis of 'Power Failure' in Neuroscience Using Mixture Modeling
Wood, John
2017-01-01
Recently, evidence for endemically low statistical power has cast neuroscience findings into doubt. If low statistical power plagues neuroscience, then this reduces confidence in the reported effects. However, if statistical power is not uniformly low, then such blanket mistrust might not be warranted. Here, we provide a different perspective on this issue, analyzing data from an influential study reporting a median power of 21% across 49 meta-analyses (Button et al., 2013). We demonstrate, using Gaussian mixture modeling, that the sample of 730 studies included in that analysis comprises several subcomponents so the use of a single summary statistic is insufficient to characterize the nature of the distribution. We find that statistical power is extremely low for studies included in meta-analyses that reported a null result and that it varies substantially across subfields of neuroscience, with particularly low power in candidate gene association studies. Therefore, whereas power in neuroscience remains a critical issue, the notion that studies are systematically underpowered is not the full story: low power is far from a universal problem. SIGNIFICANCE STATEMENT Recently, researchers across the biomedical and psychological sciences have become concerned with the reliability of results. One marker for reliability is statistical power: the probability of finding a statistically significant result given that the effect exists. Previous evidence suggests that statistical power is low across the field of neuroscience. Our results present a more comprehensive picture of statistical power in neuroscience: on average, studies are indeed underpowered—some very seriously so—but many studies show acceptable or even exemplary statistical power. We show that this heterogeneity in statistical power is common across most subfields in neuroscience. This new, more nuanced picture of statistical power in neuroscience could affect not only scientific understanding, but potentially policy and funding decisions for neuroscience research. PMID:28706080
ParallABEL: an R library for generalized parallelization of genome-wide association studies.
Sangket, Unitsa; Mahasirimongkol, Surakameth; Chantratita, Wasun; Tandayya, Pichaya; Aulchenko, Yurii S
2010-04-29
Genome-Wide Association (GWA) analysis is a powerful method for identifying loci associated with complex traits and drug response. Parts of GWA analyses, especially those involving thousands of individuals and consuming hours to months, will benefit from parallel computation. It is arduous acquiring the necessary programming skills to correctly partition and distribute data, control and monitor tasks on clustered computers, and merge output files. Most components of GWA analysis can be divided into four groups based on the types of input data and statistical outputs. The first group contains statistics computed for a particular Single Nucleotide Polymorphism (SNP), or trait, such as SNP characterization statistics or association test statistics. The input data of this group includes the SNPs/traits. The second group concerns statistics characterizing an individual in a study, for example, the summary statistics of genotype quality for each sample. The input data of this group includes individuals. The third group consists of pair-wise statistics derived from analyses between each pair of individuals in the study, for example genome-wide identity-by-state or genomic kinship analyses. The input data of this group includes pairs of SNPs/traits. The final group concerns pair-wise statistics derived for pairs of SNPs, such as the linkage disequilibrium characterisation. The input data of this group includes pairs of individuals. We developed the ParallABEL library, which utilizes the Rmpi library, to parallelize these four types of computations. ParallABEL library is not only aimed at GenABEL, but may also be employed to parallelize various GWA packages in R. The data set from the North American Rheumatoid Arthritis Consortium (NARAC) includes 2,062 individuals with 545,080, SNPs' genotyping, was used to measure ParallABEL performance. Almost perfect speed-up was achieved for many types of analyses. For example, the computing time for the identity-by-state matrix was linearly reduced from approximately eight hours to one hour when ParallABEL employed eight processors. Executing genome-wide association analysis using the ParallABEL library on a computer cluster is an effective way to boost performance, and simplify the parallelization of GWA studies. ParallABEL is a user-friendly parallelization of GenABEL.
Study Designs and Statistical Analyses for Biomarker Research
Gosho, Masahiko; Nagashima, Kengo; Sato, Yasunori
2012-01-01
Biomarkers are becoming increasingly important for streamlining drug discovery and development. In addition, biomarkers are widely expected to be used as a tool for disease diagnosis, personalized medication, and surrogate endpoints in clinical research. In this paper, we highlight several important aspects related to study design and statistical analysis for clinical research incorporating biomarkers. We describe the typical and current study designs for exploring, detecting, and utilizing biomarkers. Furthermore, we introduce statistical issues such as confounding and multiplicity for statistical tests in biomarker research. PMID:23012528
permGPU: Using graphics processing units in RNA microarray association studies.
Shterev, Ivo D; Jung, Sin-Ho; George, Stephen L; Owzar, Kouros
2010-06-16
Many analyses of microarray association studies involve permutation, bootstrap resampling and cross-validation, that are ideally formulated as embarrassingly parallel computing problems. Given that these analyses are computationally intensive, scalable approaches that can take advantage of multi-core processor systems need to be developed. We have developed a CUDA based implementation, permGPU, that employs graphics processing units in microarray association studies. We illustrate the performance and applicability of permGPU within the context of permutation resampling for a number of test statistics. An extensive simulation study demonstrates a dramatic increase in performance when using permGPU on an NVIDIA GTX 280 card compared to an optimized C/C++ solution running on a conventional Linux server. permGPU is available as an open-source stand-alone application and as an extension package for the R statistical environment. It provides a dramatic increase in performance for permutation resampling analysis in the context of microarray association studies. The current version offers six test statistics for carrying out permutation resampling analyses for binary, quantitative and censored time-to-event traits.
Harris, Michael; Radtke, Arthur S.
1976-01-01
Linear regression and discriminant analyses techniques were applied to gold, mercury, arsenic, antimony, barium, copper, molybdenum, lead, zinc, boron, tellurium, selenium, and tungsten analyses from drill holes into unoxidized gold ore at the Carlin gold mine near Carlin, Nev. The statistical treatments employed were used to judge proposed hypotheses on the origin and geochemical paragenesis of this disseminated gold deposit.
ERIC Educational Resources Information Center
Norris, John M.
2015-01-01
Traditions of statistical significance testing in second language (L2) quantitative research are strongly entrenched in how researchers design studies, select analyses, and interpret results. However, statistical significance tests using "p" values are commonly misinterpreted by researchers, reviewers, readers, and others, leading to…
Federal Register 2010, 2011, 2012, 2013, 2014
2010-05-05
...] Guidance for Industry on Documenting Statistical Analysis Programs and Data Files; Availability AGENCY... Programs and Data Files.'' This guidance is provided to inform study statisticians of recommendations for documenting statistical analyses and data files submitted to the Center for Veterinary Medicine (CVM) for the...
Performance of Between-Study Heterogeneity Measures in the Cochrane Library.
Ma, Xiaoyue; Lin, Lifeng; Qu, Zhiyong; Zhu, Motao; Chu, Haitao
2018-05-29
The growth in comparative effectiveness research and evidence-based medicine has increased attention to systematic reviews and meta-analyses. Meta-analysis synthesizes and contrasts evidence from multiple independent studies to improve statistical efficiency and reduce bias. Assessing heterogeneity is critical for performing a meta-analysis and interpreting results. As a widely used heterogeneity measure, the I statistic quantifies the proportion of total variation across studies that is due to real differences in effect size. The presence of outlying studies can seriously exaggerate the I statistic. Two alternative heterogeneity measures, the Ir and Im, have been recently proposed to reduce the impact of outlying studies. To evaluate these measures' performance empirically, we applied them to 20,599 meta-analyses in the Cochrane Library. We found that the Ir and Im have strong agreement with the I, while they are more robust than the I when outlying studies appear.
Comparing Visual and Statistical Analysis of Multiple Baseline Design Graphs.
Wolfe, Katie; Dickenson, Tammiee S; Miller, Bridget; McGrath, Kathleen V
2018-04-01
A growing number of statistical analyses are being developed for single-case research. One important factor in evaluating these methods is the extent to which each corresponds to visual analysis. Few studies have compared statistical and visual analysis, and information about more recently developed statistics is scarce. Therefore, our purpose was to evaluate the agreement between visual analysis and four statistical analyses: improvement rate difference (IRD); Tau-U; Hedges, Pustejovsky, Shadish (HPS) effect size; and between-case standardized mean difference (BC-SMD). Results indicate that IRD and BC-SMD had the strongest overall agreement with visual analysis. Although Tau-U had strong agreement with visual analysis on raw values, it had poorer agreement when those values were dichotomized to represent the presence or absence of a functional relation. Overall, visual analysis appeared to be more conservative than statistical analysis, but further research is needed to evaluate the nature of these disagreements.
Confidence crisis of results in biomechanics research.
Knudson, Duane
2017-11-01
Many biomechanics studies have small sample sizes and incorrect statistical analyses, so reporting of inaccurate inferences and inflated magnitude of effects are common in the field. This review examines these issues in biomechanics research and summarises potential solutions from research in other fields to increase the confidence in the experimental effects reported in biomechanics. Authors, reviewers and editors of biomechanics research reports are encouraged to improve sample sizes and the resulting statistical power, improve reporting transparency, improve the rigour of statistical analyses used, and increase the acceptance of replication studies to improve the validity of inferences from data in biomechanics research. The application of sports biomechanics research results would also improve if a larger percentage of unbiased effects and their uncertainty were reported in the literature.
Coordinate based random effect size meta-analysis of neuroimaging studies.
Tench, C R; Tanasescu, Radu; Constantinescu, C S; Auer, D P; Cottam, W J
2017-06-01
Low power in neuroimaging studies can make them difficult to interpret, and Coordinate based meta-analysis (CBMA) may go some way to mitigating this issue. CBMA has been used in many analyses to detect where published functional MRI or voxel-based morphometry studies testing similar hypotheses report significant summary results (coordinates) consistently. Only the reported coordinates and possibly t statistics are analysed, and statistical significance of clusters is determined by coordinate density. Here a method of performing coordinate based random effect size meta-analysis and meta-regression is introduced. The algorithm (ClusterZ) analyses both coordinates and reported t statistic or Z score, standardised by the number of subjects. Statistical significance is determined not by coordinate density, but by a random effects meta-analyses of reported effects performed cluster-wise using standard statistical methods and taking account of censoring inherent in the published summary results. Type 1 error control is achieved using the false cluster discovery rate (FCDR), which is based on the false discovery rate. This controls both the family wise error rate under the null hypothesis that coordinates are randomly drawn from a standard stereotaxic space, and the proportion of significant clusters that are expected under the null. Such control is necessary to avoid propagating and even amplifying the very issues motivating the meta-analysis in the first place. ClusterZ is demonstrated on both numerically simulated data and on real data from reports of grey matter loss in multiple sclerosis (MS) and syndromes suggestive of MS, and of painful stimulus in healthy controls. The software implementation is available to download and use freely. Copyright © 2017 Elsevier Inc. All rights reserved.
The Australasian Resuscitation in Sepsis Evaluation (ARISE) trial statistical analysis plan.
Delaney, Anthony P; Peake, Sandra L; Bellomo, Rinaldo; Cameron, Peter; Holdgate, Anna; Howe, Belinda; Higgins, Alisa; Presneill, Jeffrey; Webb, Steve
2013-09-01
The Australasian Resuscitation in Sepsis Evaluation (ARISE) study is an international, multicentre, randomised, controlled trial designed to evaluate the effectiveness of early goal-directed therapy compared with standard care for patients presenting to the emergency department with severe sepsis. In keeping with current practice, and considering aspects of trial design and reporting specific to non-pharmacological interventions, our plan outlines the principles and methods for analysing and reporting the trial results. The document is prepared before completion of recruitment into the ARISE study, without knowledge of the results of the interim analysis conducted by the data safety and monitoring committee and before completion of the two related international studies. Our statistical analysis plan was designed by the ARISE chief investigators, and reviewed and approved by the ARISE steering committee. We reviewed the data collected by the research team as specified in the study protocol and detailed in the study case report form. We describe information related to baseline characteristics, characteristics of delivery of the trial interventions, details of resuscitation, other related therapies and other relevant data with appropriate comparisons between groups. We define the primary, secondary and tertiary outcomes for the study, with description of the planned statistical analyses. We have developed a statistical analysis plan with a trial profile, mock-up tables and figures. We describe a plan for presenting baseline characteristics, microbiological and antibiotic therapy, details of the interventions, processes of care and concomitant therapies and adverse events. We describe the primary, secondary and tertiary outcomes with identification of subgroups to be analysed. We have developed a statistical analysis plan for the ARISE study, available in the public domain, before the completion of recruitment into the study. This will minimise analytical bias and conforms to current best practice in conducting clinical trials.
ERIC Educational Resources Information Center
Wiggins, Lyna; Nower, Lia; Mayers, Raymond Sanchez; Peterson, N. Andrew
2010-01-01
This study examines the density of lottery outlets within ethnically concentrated neighborhoods in Middlesex County, New Jersey, using geospatial statistical analyses. No prior studies have empirically examined the relationship between lottery outlet density and population demographics. Results indicate that lottery outlets were not randomly…
de Sá, Joceline Cássia Ferezini; Marini, Gabriela; Gelaleti, Rafael Bottaro; da Silva, João Batista; de Azevedo, George Gantas; Rudge, Marilza Vieira Cunha
2013-11-01
To evaluate the methodological and statistical design evolution of the publications in the Brazilian Journal of Gynecology and Obstetrics (RBGO) from resolution 196/96. A review of 133 articles published in 1999 (65) and 2009 (68) was performed by two independent reviewers with training in clinical epidemiology and methodology of scientific research. We included all original clinical articles, case and series reports and excluded editorials, letters to the editor, systematic reviews, experimental studies, opinion articles, besides abstracts of theses and dissertations. Characteristics related to the methodological quality of the studies were analyzed in each article using a checklist that evaluated two criteria: methodological aspects and statistical procedures. We used descriptive statistics and the χ2 test for comparison of the two years. There was a difference between 1999 and 2009 regarding the study and statistical design, with more accuracy in the procedures and the use of more robust tests between 1999 and 2009. In RBGO, we observed an evolution in the methods of published articles and a more in-depth use of the statistical analyses, with more sophisticated tests such as regression and multilevel analyses, which are essential techniques for the knowledge and planning of health interventions, leading to fewer interpretation errors.
Power-up: A Reanalysis of 'Power Failure' in Neuroscience Using Mixture Modeling.
Nord, Camilla L; Valton, Vincent; Wood, John; Roiser, Jonathan P
2017-08-23
Recently, evidence for endemically low statistical power has cast neuroscience findings into doubt. If low statistical power plagues neuroscience, then this reduces confidence in the reported effects. However, if statistical power is not uniformly low, then such blanket mistrust might not be warranted. Here, we provide a different perspective on this issue, analyzing data from an influential study reporting a median power of 21% across 49 meta-analyses (Button et al., 2013). We demonstrate, using Gaussian mixture modeling, that the sample of 730 studies included in that analysis comprises several subcomponents so the use of a single summary statistic is insufficient to characterize the nature of the distribution. We find that statistical power is extremely low for studies included in meta-analyses that reported a null result and that it varies substantially across subfields of neuroscience, with particularly low power in candidate gene association studies. Therefore, whereas power in neuroscience remains a critical issue, the notion that studies are systematically underpowered is not the full story: low power is far from a universal problem. SIGNIFICANCE STATEMENT Recently, researchers across the biomedical and psychological sciences have become concerned with the reliability of results. One marker for reliability is statistical power: the probability of finding a statistically significant result given that the effect exists. Previous evidence suggests that statistical power is low across the field of neuroscience. Our results present a more comprehensive picture of statistical power in neuroscience: on average, studies are indeed underpowered-some very seriously so-but many studies show acceptable or even exemplary statistical power. We show that this heterogeneity in statistical power is common across most subfields in neuroscience. This new, more nuanced picture of statistical power in neuroscience could affect not only scientific understanding, but potentially policy and funding decisions for neuroscience research. Copyright © 2017 Nord, Valton et al.
ParallABEL: an R library for generalized parallelization of genome-wide association studies
2010-01-01
Background Genome-Wide Association (GWA) analysis is a powerful method for identifying loci associated with complex traits and drug response. Parts of GWA analyses, especially those involving thousands of individuals and consuming hours to months, will benefit from parallel computation. It is arduous acquiring the necessary programming skills to correctly partition and distribute data, control and monitor tasks on clustered computers, and merge output files. Results Most components of GWA analysis can be divided into four groups based on the types of input data and statistical outputs. The first group contains statistics computed for a particular Single Nucleotide Polymorphism (SNP), or trait, such as SNP characterization statistics or association test statistics. The input data of this group includes the SNPs/traits. The second group concerns statistics characterizing an individual in a study, for example, the summary statistics of genotype quality for each sample. The input data of this group includes individuals. The third group consists of pair-wise statistics derived from analyses between each pair of individuals in the study, for example genome-wide identity-by-state or genomic kinship analyses. The input data of this group includes pairs of SNPs/traits. The final group concerns pair-wise statistics derived for pairs of SNPs, such as the linkage disequilibrium characterisation. The input data of this group includes pairs of individuals. We developed the ParallABEL library, which utilizes the Rmpi library, to parallelize these four types of computations. ParallABEL library is not only aimed at GenABEL, but may also be employed to parallelize various GWA packages in R. The data set from the North American Rheumatoid Arthritis Consortium (NARAC) includes 2,062 individuals with 545,080, SNPs' genotyping, was used to measure ParallABEL performance. Almost perfect speed-up was achieved for many types of analyses. For example, the computing time for the identity-by-state matrix was linearly reduced from approximately eight hours to one hour when ParallABEL employed eight processors. Conclusions Executing genome-wide association analysis using the ParallABEL library on a computer cluster is an effective way to boost performance, and simplify the parallelization of GWA studies. ParallABEL is a user-friendly parallelization of GenABEL. PMID:20429914
SOCR Analyses - an Instructional Java Web-based Statistical Analysis Toolkit.
Chu, Annie; Cui, Jenny; Dinov, Ivo D
2009-03-01
The Statistical Online Computational Resource (SOCR) designs web-based tools for educational use in a variety of undergraduate courses (Dinov 2006). Several studies have demonstrated that these resources significantly improve students' motivation and learning experiences (Dinov et al. 2008). SOCR Analyses is a new component that concentrates on data modeling and analysis using parametric and non-parametric techniques supported with graphical model diagnostics. Currently implemented analyses include commonly used models in undergraduate statistics courses like linear models (Simple Linear Regression, Multiple Linear Regression, One-Way and Two-Way ANOVA). In addition, we implemented tests for sample comparisons, such as t-test in the parametric category; and Wilcoxon rank sum test, Kruskal-Wallis test, Friedman's test, in the non-parametric category. SOCR Analyses also include several hypothesis test models, such as Contingency tables, Friedman's test and Fisher's exact test.The code itself is open source (http://socr.googlecode.com/), hoping to contribute to the efforts of the statistical computing community. The code includes functionality for each specific analysis model and it has general utilities that can be applied in various statistical computing tasks. For example, concrete methods with API (Application Programming Interface) have been implemented in statistical summary, least square solutions of general linear models, rank calculations, etc. HTML interfaces, tutorials, source code, activities, and data are freely available via the web (www.SOCR.ucla.edu). Code examples for developers and demos for educators are provided on the SOCR Wiki website.In this article, the pedagogical utilization of the SOCR Analyses is discussed, as well as the underlying design framework. As the SOCR project is on-going and more functions and tools are being added to it, these resources are constantly improved. The reader is strongly encouraged to check the SOCR site for most updated information and newly added models.
ERIC Educational Resources Information Center
Plonsky, Luke
2013-01-01
This study assesses research and reporting practices in quantitative second language (L2) research. A sample of 606 primary studies, published from 1990 to 2010 in "Language Learning and Studies in Second Language Acquisition," was collected and coded for designs, statistical analyses, reporting practices, and outcomes (i.e., effect…
Formalizing the definition of meta-analysis in Molecular Ecology.
ArchMiller, Althea A; Bauer, Eric F; Koch, Rebecca E; Wijayawardena, Bhagya K; Anil, Ammu; Kottwitz, Jack J; Munsterman, Amelia S; Wilson, Alan E
2015-08-01
Meta-analysis, the statistical synthesis of pertinent literature to develop evidence-based conclusions, is relatively new to the field of molecular ecology, with the first meta-analysis published in the journal Molecular Ecology in 2003 (Slate & Phua 2003). The goal of this article is to formalize the definition of meta-analysis for the authors, editors, reviewers and readers of Molecular Ecology by completing a review of the meta-analyses previously published in this journal. We also provide a brief overview of the many components required for meta-analysis with a more specific discussion of the issues related to the field of molecular ecology, including the use and statistical considerations of Wright's FST and its related analogues as effect sizes in meta-analysis. We performed a literature review to identify articles published as 'meta-analyses' in Molecular Ecology, which were then evaluated by at least two reviewers. We specifically targeted Molecular Ecology publications because as a flagship journal in this field, meta-analyses published in Molecular Ecology have the potential to set the standard for meta-analyses in other journals. We found that while many of these reviewed articles were strong meta-analyses, others failed to follow standard meta-analytical techniques. One of these unsatisfactory meta-analyses was in fact a secondary analysis. Other studies attempted meta-analyses but lacked the fundamental statistics that are considered necessary for an effective and powerful meta-analysis. By drawing attention to the inconsistency of studies labelled as meta-analyses, we emphasize the importance of understanding the components of traditional meta-analyses to fully embrace the strengths of quantitative data synthesis in the field of molecular ecology. © 2015 John Wiley & Sons Ltd.
Willis, Brian H; Riley, Richard D
2017-09-20
An important question for clinicians appraising a meta-analysis is: are the findings likely to be valid in their own practice-does the reported effect accurately represent the effect that would occur in their own clinical population? To this end we advance the concept of statistical validity-where the parameter being estimated equals the corresponding parameter for a new independent study. Using a simple ('leave-one-out') cross-validation technique, we demonstrate how we may test meta-analysis estimates for statistical validity using a new validation statistic, Vn, and derive its distribution. We compare this with the usual approach of investigating heterogeneity in meta-analyses and demonstrate the link between statistical validity and homogeneity. Using a simulation study, the properties of Vn and the Q statistic are compared for univariate random effects meta-analysis and a tailored meta-regression model, where information from the setting (included as model covariates) is used to calibrate the summary estimate to the setting of application. Their properties are found to be similar when there are 50 studies or more, but for fewer studies Vn has greater power but a higher type 1 error rate than Q. The power and type 1 error rate of Vn are also shown to depend on the within-study variance, between-study variance, study sample size, and the number of studies in the meta-analysis. Finally, we apply Vn to two published meta-analyses and conclude that it usefully augments standard methods when deciding upon the likely validity of summary meta-analysis estimates in clinical practice. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.
Logistic regression applied to natural hazards: rare event logistic regression with replications
NASA Astrophysics Data System (ADS)
Guns, M.; Vanacker, V.
2012-06-01
Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logistic regression with replications, combines the strength of probabilistic and statistical methods, and allows overcoming some of the limitations of previous developments through robust variable selection. This technique was here developed for the analyses of landslide controlling factors, but the concept is widely applicable for statistical analyses of natural hazards.
Gadbury, Gary L.; Allison, David B.
2012-01-01
Much has been written regarding p-values below certain thresholds (most notably 0.05) denoting statistical significance and the tendency of such p-values to be more readily publishable in peer-reviewed journals. Intuition suggests that there may be a tendency to manipulate statistical analyses to push a “near significant p-value” to a level that is considered significant. This article presents a method for detecting the presence of such manipulation (herein called “fiddling”) in a distribution of p-values from independent studies. Simulations are used to illustrate the properties of the method. The results suggest that the method has low type I error and that power approaches acceptable levels as the number of p-values being studied approaches 1000. PMID:23056287
Gadbury, Gary L; Allison, David B
2012-01-01
Much has been written regarding p-values below certain thresholds (most notably 0.05) denoting statistical significance and the tendency of such p-values to be more readily publishable in peer-reviewed journals. Intuition suggests that there may be a tendency to manipulate statistical analyses to push a "near significant p-value" to a level that is considered significant. This article presents a method for detecting the presence of such manipulation (herein called "fiddling") in a distribution of p-values from independent studies. Simulations are used to illustrate the properties of the method. The results suggest that the method has low type I error and that power approaches acceptable levels as the number of p-values being studied approaches 1000.
Progressive statistics for studies in sports medicine and exercise science.
Hopkins, William G; Marshall, Stephen W; Batterham, Alan M; Hanin, Juri
2009-01-01
Statistical guidelines and expert statements are now available to assist in the analysis and reporting of studies in some biomedical disciplines. We present here a more progressive resource for sample-based studies, meta-analyses, and case studies in sports medicine and exercise science. We offer forthright advice on the following controversial or novel issues: using precision of estimation for inferences about population effects in preference to null-hypothesis testing, which is inadequate for assessing clinical or practical importance; justifying sample size via acceptable precision or confidence for clinical decisions rather than via adequate power for statistical significance; showing SD rather than SEM, to better communicate the magnitude of differences in means and nonuniformity of error; avoiding purely nonparametric analyses, which cannot provide inferences about magnitude and are unnecessary; using regression statistics in validity studies, in preference to the impractical and biased limits of agreement; making greater use of qualitative methods to enrich sample-based quantitative projects; and seeking ethics approval for public access to the depersonalized raw data of a study, to address the need for more scrutiny of research and better meta-analyses. Advice on less contentious issues includes the following: using covariates in linear models to adjust for confounders, to account for individual differences, and to identify potential mechanisms of an effect; using log transformation to deal with nonuniformity of effects and error; identifying and deleting outliers; presenting descriptive, effect, and inferential statistics in appropriate formats; and contending with bias arising from problems with sampling, assignment, blinding, measurement error, and researchers' prejudices. This article should advance the field by stimulating debate, promoting innovative approaches, and serving as a useful checklist for authors, reviewers, and editors.
ERIC Educational Resources Information Center
Karazsia, Bryan T.; Wong, Kendal
2016-01-01
Quantitative and statistical literacy are core domains in the undergraduate psychology curriculum. An important component of such literacy includes interpretation of visual aids, such as tables containing results from statistical analyses. This article presents results of a quasi-experimental study with longitudinal follow-up that tested the…
Kelley, George A.; Kelley, Kristi S.
2013-01-01
Purpose. Conduct a systematic review of previous meta-analyses addressing the effects of exercise in the treatment of overweight and obese children and adolescents. Methods. Previous meta-analyses of randomized controlled exercise trials that assessed adiposity in overweight and obese children and adolescents were included by searching nine electronic databases and cross-referencing from retrieved studies. Methodological quality was assessed using the Assessment of Multiple Systematic Reviews (AMSTAR) Instrument. The alpha level for statistical significance was set at P ≤ 0.05. Results. Of the 308 studies reviewed, two aggregate data meta-analyses representing 14 and 17 studies and 481 and 701 boys and girls met all eligibility criteria. Methodological quality was 64% and 73%. For both studies, statistically significant reductions in percent body fat were observed (P = 0.006 and P < 0.00001). The number-needed-to treat (NNT) was 4 and 3 with an estimated 24.5 and 31.5 million overweight and obese children in the world potentially benefitting, 2.8 and 3.6 million in the US. No other measures of adiposity (BMI-related measures, body weight, and central obesity) were statistically significant. Conclusions. Exercise is efficacious for reducing percent body fat in overweight and obese children and adolescents. Insufficient evidence exists to suggest that exercise reduces other measures of adiposity. PMID:24455215
Evaluation and application of summary statistic imputation to discover new height-associated loci.
Rüeger, Sina; McDaid, Aaron; Kutalik, Zoltán
2018-05-01
As most of the heritability of complex traits is attributed to common and low frequency genetic variants, imputing them by combining genotyping chips and large sequenced reference panels is the most cost-effective approach to discover the genetic basis of these traits. Association summary statistics from genome-wide meta-analyses are available for hundreds of traits. Updating these to ever-increasing reference panels is very cumbersome as it requires reimputation of the genetic data, rerunning the association scan, and meta-analysing the results. A much more efficient method is to directly impute the summary statistics, termed as summary statistics imputation, which we improved to accommodate variable sample size across SNVs. Its performance relative to genotype imputation and practical utility has not yet been fully investigated. To this end, we compared the two approaches on real (genotyped and imputed) data from 120K samples from the UK Biobank and show that, genotype imputation boasts a 3- to 5-fold lower root-mean-square error, and better distinguishes true associations from null ones: We observed the largest differences in power for variants with low minor allele frequency and low imputation quality. For fixed false positive rates of 0.001, 0.01, 0.05, using summary statistics imputation yielded a decrease in statistical power by 9, 43 and 35%, respectively. To test its capacity to discover novel associations, we applied summary statistics imputation to the GIANT height meta-analysis summary statistics covering HapMap variants, and identified 34 novel loci, 19 of which replicated using data in the UK Biobank. Additionally, we successfully replicated 55 out of the 111 variants published in an exome chip study. Our study demonstrates that summary statistics imputation is a very efficient and cost-effective way to identify and fine-map trait-associated loci. Moreover, the ability to impute summary statistics is important for follow-up analyses, such as Mendelian randomisation or LD-score regression.
Evaluation and application of summary statistic imputation to discover new height-associated loci
2018-01-01
As most of the heritability of complex traits is attributed to common and low frequency genetic variants, imputing them by combining genotyping chips and large sequenced reference panels is the most cost-effective approach to discover the genetic basis of these traits. Association summary statistics from genome-wide meta-analyses are available for hundreds of traits. Updating these to ever-increasing reference panels is very cumbersome as it requires reimputation of the genetic data, rerunning the association scan, and meta-analysing the results. A much more efficient method is to directly impute the summary statistics, termed as summary statistics imputation, which we improved to accommodate variable sample size across SNVs. Its performance relative to genotype imputation and practical utility has not yet been fully investigated. To this end, we compared the two approaches on real (genotyped and imputed) data from 120K samples from the UK Biobank and show that, genotype imputation boasts a 3- to 5-fold lower root-mean-square error, and better distinguishes true associations from null ones: We observed the largest differences in power for variants with low minor allele frequency and low imputation quality. For fixed false positive rates of 0.001, 0.01, 0.05, using summary statistics imputation yielded a decrease in statistical power by 9, 43 and 35%, respectively. To test its capacity to discover novel associations, we applied summary statistics imputation to the GIANT height meta-analysis summary statistics covering HapMap variants, and identified 34 novel loci, 19 of which replicated using data in the UK Biobank. Additionally, we successfully replicated 55 out of the 111 variants published in an exome chip study. Our study demonstrates that summary statistics imputation is a very efficient and cost-effective way to identify and fine-map trait-associated loci. Moreover, the ability to impute summary statistics is important for follow-up analyses, such as Mendelian randomisation or LD-score regression. PMID:29782485
Differences in Performance Among Test Statistics for Assessing Phylogenomic Model Adequacy.
Duchêne, David A; Duchêne, Sebastian; Ho, Simon Y W
2018-05-18
Statistical phylogenetic analyses of genomic data depend on models of nucleotide or amino acid substitution. The adequacy of these substitution models can be assessed using a number of test statistics, allowing the model to be rejected when it is found to provide a poor description of the evolutionary process. A potentially valuable use of model-adequacy test statistics is to identify when data sets are likely to produce unreliable phylogenetic estimates, but their differences in performance are rarely explored. We performed a comprehensive simulation study to identify test statistics that are sensitive to some of the most commonly cited sources of phylogenetic estimation error. Our results show that, for many test statistics, traditional thresholds for assessing model adequacy can fail to reject the model when the phylogenetic inferences are inaccurate and imprecise. This is particularly problematic when analysing loci that have few variable informative sites. We propose new thresholds for assessing substitution model adequacy and demonstrate their effectiveness in analyses of three phylogenomic data sets. These thresholds lead to frequent rejection of the model for loci that yield topological inferences that are imprecise and are likely to be inaccurate. We also propose the use of a summary statistic that provides a practical assessment of overall model adequacy. Our approach offers a promising means of enhancing model choice in genome-scale data sets, potentially leading to improvements in the reliability of phylogenomic inference.
Nimptsch, Ulrike; Wengler, Annelene; Mansky, Thomas
2016-11-01
In Germany, nationwide hospital discharge data (DRG statistics provided by the research data centers of the Federal Statistical Office and the Statistical Offices of the 'Länder') are increasingly used as data source for health services research. Within this data hospitals can be separated via their hospital identifier ([Institutionskennzeichen] IK). However, this hospital identifier primarily designates the invoicing unit and is not necessarily equivalent to one hospital location. Aiming to investigate direction and extent of possible bias in hospital-level analyses this study examines the continuity of the hospital identifier within a cross-sectional and longitudinal approach and compares the results to official hospital census statistics. Within the DRG statistics from 2005 to 2013 the annual number of hospitals as classified by hospital identifiers was counted for each year of observation. The annual number of hospitals derived from DRG statistics was compared to the number of hospitals in the official census statistics 'Grunddaten der Krankenhäuser'. Subsequently, the temporal continuity of hospital identifiers in the DRG statistics was analyzed within cohorts of hospitals. Until 2013, the annual number of hospital identifiers in the DRG statistics fell by 175 (from 1,725 to 1,550). This decline affected only providers with small or medium case volume. The number of hospitals identified in the DRG statistics was lower than the number given in the census statistics (e.g., in 2013 1,550 IK vs. 1,668 hospitals in the census statistics). The longitudinal analyses revealed that the majority of hospital identifiers persisted in the years of observation, while one fifth of hospital identifiers changed. In cross-sectional studies of German hospital discharge data the separation of hospitals via the hospital identifier might lead to underestimating the number of hospitals and consequential overestimation of caseload per hospital. Discontinuities of hospital identifiers over time might impair the follow-up of hospital cohorts. These limitations must be taken into account in analyses of German hospital discharge data focusing on the hospital level. Copyright © 2016. Published by Elsevier GmbH.
"What If" Analyses: Ways to Interpret Statistical Significance Test Results Using EXCEL or "R"
ERIC Educational Resources Information Center
Ozturk, Elif
2012-01-01
The present paper aims to review two motivations to conduct "what if" analyses using Excel and "R" to understand the statistical significance tests through the sample size context. "What if" analyses can be used to teach students what statistical significance tests really do and in applied research either prospectively to estimate what sample size…
Ensor, Joie; Riley, Richard D.
2016-01-01
Meta‐analysis using individual participant data (IPD) obtains and synthesises the raw, participant‐level data from a set of relevant studies. The IPD approach is becoming an increasingly popular tool as an alternative to traditional aggregate data meta‐analysis, especially as it avoids reliance on published results and provides an opportunity to investigate individual‐level interactions, such as treatment‐effect modifiers. There are two statistical approaches for conducting an IPD meta‐analysis: one‐stage and two‐stage. The one‐stage approach analyses the IPD from all studies simultaneously, for example, in a hierarchical regression model with random effects. The two‐stage approach derives aggregate data (such as effect estimates) in each study separately and then combines these in a traditional meta‐analysis model. There have been numerous comparisons of the one‐stage and two‐stage approaches via theoretical consideration, simulation and empirical examples, yet there remains confusion regarding when each approach should be adopted, and indeed why they may differ. In this tutorial paper, we outline the key statistical methods for one‐stage and two‐stage IPD meta‐analyses, and provide 10 key reasons why they may produce different summary results. We explain that most differences arise because of different modelling assumptions, rather than the choice of one‐stage or two‐stage itself. We illustrate the concepts with recently published IPD meta‐analyses, summarise key statistical software and provide recommendations for future IPD meta‐analyses. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. PMID:27747915
Reframing Serial Murder Within Empirical Research.
Gurian, Elizabeth A
2017-04-01
Empirical research on serial murder is limited due to the lack of consensus on a definition, the continued use of primarily descriptive statistics, and linkage to popular culture depictions. These limitations also inhibit our understanding of these offenders and affect credibility in the field of research. Therefore, this comprehensive overview of a sample of 508 cases (738 total offenders, including partnered groups of two or more offenders) provides analyses of solo male, solo female, and partnered serial killers to elucidate statistical differences and similarities in offending and adjudication patterns among the three groups. This analysis of serial homicide offenders not only supports previous research on offending patterns present in the serial homicide literature but also reveals that empirically based analyses can enhance our understanding beyond traditional case studies and descriptive statistics. Further research based on these empirical analyses can aid in the development of more accurate classifications and definitions of serial murderers.
Barbie, Dana L.; Wehmeyer, Loren L.
2012-01-01
Trends in selected streamflow statistics during 1922-2009 were evaluated at 19 long-term streamflow-gaging stations considered indicative of outflows from Texas to Arkansas, Louisiana, Galveston Bay, and the Gulf of Mexico. The U.S. Geological Survey, in cooperation with the Texas Water Development Board, evaluated streamflow data from streamflow-gaging stations with more than 50 years of record that were active as of 2009. The outflows into Arkansas and Louisiana were represented by 3 streamflow-gaging stations, and outflows into the Gulf of Mexico, including Galveston Bay, were represented by 16 streamflow-gaging stations. Monotonic trend analyses were done using the following three streamflow statistics generated from daily mean values of streamflow: (1) annual mean daily discharge, (2) annual maximum daily discharge, and (3) annual minimum daily discharge. The trend analyses were based on the nonparametric Kendall's Tau test, which is useful for the detection of monotonic upward or downward trends with time. A total of 69 trend analyses by Kendall's Tau were computed - 19 periods of streamflow multiplied by the 3 streamflow statistics plus 12 additional trend analyses because the periods of record for 2 streamflow-gaging stations were divided into periods representing pre- and post-reservoir impoundment. Unless otherwise described, each trend analysis used the entire period of record for each streamflow-gaging station. The monotonic trend analysis detected 11 statistically significant downward trends, 37 instances of no trend, and 21 statistically significant upward trends. One general region studied, which seemingly has relatively more upward trends for many of the streamflow statistics analyzed, includes the rivers and associated creeks and bayous to Galveston Bay in the Houston metropolitan area. Lastly, the most western river basins considered (the Nueces and Rio Grande) had statistically significant downward trends for many of the streamflow statistics analyzed.
Thompson, Ronald E.; Hoffman, Scott A.
2006-01-01
A suite of 28 streamflow statistics, ranging from extreme low to high flows, was computed for 17 continuous-record streamflow-gaging stations and predicted for 20 partial-record stations in Monroe County and contiguous counties in north-eastern Pennsylvania. The predicted statistics for the partial-record stations were based on regression analyses relating inter-mittent flow measurements made at the partial-record stations indexed to concurrent daily mean flows at continuous-record stations during base-flow conditions. The same statistics also were predicted for 134 ungaged stream locations in Monroe County on the basis of regression analyses relating the statistics to GIS-determined basin characteristics for the continuous-record station drainage areas. The prediction methodology for developing the regression equations used to estimate statistics was developed for estimating low-flow frequencies. This study and a companion study found that the methodology also has application potential for predicting intermediate- and high-flow statistics. The statistics included mean monthly flows, mean annual flow, 7-day low flows for three recurrence intervals, nine flow durations, mean annual base flow, and annual mean base flows for two recurrence intervals. Low standard errors of prediction and high coefficients of determination (R2) indicated good results in using the regression equations to predict the statistics. Regression equations for the larger flow statistics tended to have lower standard errors of prediction and higher coefficients of determination (R2) than equations for the smaller flow statistics. The report discusses the methodologies used in determining the statistics and the limitations of the statistics and the equations used to predict the statistics. Caution is indicated in using the predicted statistics for small drainage area situations. Study results constitute input needed by water-resource managers in Monroe County for planning purposes and evaluation of water-resources availability.
ERIC Educational Resources Information Center
Dahabreh, Issa J.; Chung, Mei; Kitsios, Georgios D.; Terasawa, Teruhiko; Raman, Gowri; Tatsioni, Athina; Tobar, Annette; Lau, Joseph; Trikalinos, Thomas A.; Schmid, Christopher H.
2013-01-01
We performed a survey of meta-analyses of test performance to describe the evolution in their methods and reporting. Studies were identified through MEDLINE (1966-2009), reference lists, and relevant reviews. We extracted information on clinical topics, literature review methods, quality assessment, and statistical analyses. We reviewed 760…
Statistics for Learning Genetics
ERIC Educational Resources Information Center
Charles, Abigail Sheena
2012-01-01
This study investigated the knowledge and skills that biology students may need to help them understand statistics/mathematics as it applies to genetics. The data are based on analyses of current representative genetics texts, practicing genetics professors' perspectives, and more directly, students' perceptions of, and performance in, doing…
Targeted On-Demand Team Performance App Development
2016-10-01
from three sites; 6) Preliminary analysis indicates larger than estimate effect size and study is sufficiently powered for generalizable outcomes...statistical analyses, and examine any resulting qualitative data for trends or connections to statistical outcomes. On Schedule 21 Predictive...Preliminary analysis indicates larger than estimate effect size and study is sufficiently powered for generalizable outcomes. What opportunities for
From sexless to sexy: Why it is time for human genetics to consider and report analyses of sex.
Powers, Matthew S; Smith, Phillip H; McKee, Sherry A; Ehringer, Marissa A
2017-01-01
Science has come a long way with regard to the consideration of sex differences in clinical and preclinical research, but one field remains behind the curve: human statistical genetics. The goal of this commentary is to raise awareness and discussion about how to best consider and evaluate possible sex effects in the context of large-scale human genetic studies. Over the course of this commentary, we reinforce the importance of interpreting genetic results in the context of biological sex, establish evidence that sex differences are not being considered in human statistical genetics, and discuss how best to conduct and report such analyses. Our recommendation is to run stratified analyses by sex no matter the sample size or the result and report the findings. Summary statistics from stratified analyses are helpful for meta-analyses, and patterns of sex-dependent associations may be hidden in a combined dataset. In the age of declining sequencing costs, large consortia efforts, and a number of useful control samples, it is now time for the field of human genetics to appropriately include sex in the design, analysis, and reporting of results.
Statistics for Radiology Research.
Obuchowski, Nancy A; Subhas, Naveen; Polster, Joshua
2017-02-01
Biostatistics is an essential component in most original research studies in imaging. In this article we discuss five key statistical concepts for study design and analyses in modern imaging research: statistical hypothesis testing, particularly focusing on noninferiority studies; imaging outcomes especially when there is no reference standard; dealing with the multiplicity problem without spending all your study power; relevance of confidence intervals in reporting and interpreting study results; and finally tools for assessing quantitative imaging biomarkers. These concepts are presented first as examples of conversations between investigator and biostatistician, and then more detailed discussions of the statistical concepts follow. Three skeletal radiology examples are used to illustrate the concepts. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.
Vieira, Rute; McDonald, Suzanne; Araújo-Soares, Vera; Sniehotta, Falko F; Henderson, Robin
2017-09-01
N-of-1 studies are based on repeated observations within an individual or unit over time and are acknowledged as an important research method for generating scientific evidence about the health or behaviour of an individual. Statistical analyses of n-of-1 data require accurate modelling of the outcome while accounting for its distribution, time-related trend and error structures (e.g., autocorrelation) as well as reporting readily usable contextualised effect sizes for decision-making. A number of statistical approaches have been documented but no consensus exists on which method is most appropriate for which type of n-of-1 design. We discuss the statistical considerations for analysing n-of-1 studies and briefly review some currently used methodologies. We describe dynamic regression modelling as a flexible and powerful approach, adaptable to different types of outcomes and capable of dealing with the different challenges inherent to n-of-1 statistical modelling. Dynamic modelling borrows ideas from longitudinal and event history methodologies which explicitly incorporate the role of time and the influence of past on future. We also present an illustrative example of the use of dynamic regression on monitoring physical activity during the retirement transition. Dynamic modelling has the potential to expand researchers' access to robust and user-friendly statistical methods for individualised studies.
Riley, Richard D.
2017-01-01
An important question for clinicians appraising a meta‐analysis is: are the findings likely to be valid in their own practice—does the reported effect accurately represent the effect that would occur in their own clinical population? To this end we advance the concept of statistical validity—where the parameter being estimated equals the corresponding parameter for a new independent study. Using a simple (‘leave‐one‐out’) cross‐validation technique, we demonstrate how we may test meta‐analysis estimates for statistical validity using a new validation statistic, Vn, and derive its distribution. We compare this with the usual approach of investigating heterogeneity in meta‐analyses and demonstrate the link between statistical validity and homogeneity. Using a simulation study, the properties of Vn and the Q statistic are compared for univariate random effects meta‐analysis and a tailored meta‐regression model, where information from the setting (included as model covariates) is used to calibrate the summary estimate to the setting of application. Their properties are found to be similar when there are 50 studies or more, but for fewer studies Vn has greater power but a higher type 1 error rate than Q. The power and type 1 error rate of Vn are also shown to depend on the within‐study variance, between‐study variance, study sample size, and the number of studies in the meta‐analysis. Finally, we apply Vn to two published meta‐analyses and conclude that it usefully augments standard methods when deciding upon the likely validity of summary meta‐analysis estimates in clinical practice. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. PMID:28620945
Dexter, Franklin; Shafer, Steven L
2017-03-01
Considerable attention has been drawn to poor reproducibility in the biomedical literature. One explanation is inadequate reporting of statistical methods by authors and inadequate assessment of statistical reporting and methods during peer review. In this narrative review, we examine scientific studies of several well-publicized efforts to improve statistical reporting. We also review several retrospective assessments of the impact of these efforts. These studies show that instructions to authors and statistical checklists are not sufficient; no findings suggested that either improves the quality of statistical methods and reporting. Second, even basic statistics, such as power analyses, are frequently missing or incorrectly performed. Third, statistical review is needed for all papers that involve data analysis. A consistent finding in the studies was that nonstatistical reviewers (eg, "scientific reviewers") and journal editors generally poorly assess statistical quality. We finish by discussing our experience with statistical review at Anesthesia & Analgesia from 2006 to 2016.
Mali, Matilda; Dell'Anna, Maria Michela; Mastrorilli, Piero; Damiani, Leonardo; Ungaro, Nicola; Belviso, Claudia; Fiore, Saverio
2015-11-01
Sediment contamination by metals poses significant risks to coastal ecosystems and is considered to be problematic for dredging operations. The determination of the background values of metal and metalloid distribution based on site-specific variability is fundamental in assessing pollution levels in harbour sediments. The novelty of the present work consists of addressing the scope and limitation of analysing port sediments through the use of conventional statistical techniques (such as: linear regression analysis, construction of cumulative frequency curves and the iterative 2σ technique), that are commonly employed for assessing Regional Geochemical Background (RGB) values in coastal sediments. This study ascertained that although the tout court use of such techniques in determining the RGB values in harbour sediments seems appropriate (the chemical-physical parameters of port sediments fit well with statistical equations), it should nevertheless be avoided because it may be misleading and can mask key aspects of the study area that can only be revealed by further investigations, such as mineralogical and multivariate statistical analyses. Copyright © 2015 Elsevier Ltd. All rights reserved.
Cavalcante, Y L; Hauser-Davis, R A; Saraiva, A C F; Brandão, I L S; Oliveira, T F; Silveira, A M
2013-01-01
This paper compared and evaluated seasonal variations in physico-chemical parameters and metals at a hydroelectric power station reservoir by applying Multivariate Analyses and Artificial Neural Networks (ANN) statistical techniques. A Factor Analysis was used to reduce the number of variables: the first factor was composed of elements Ca, K, Mg and Na, and the second by Chemical Oxygen Demand. The ANN showed 100% correct classifications in training and validation samples. Physico-chemical analyses showed that water pH values were not statistically different between the dry and rainy seasons, while temperature, conductivity, alkalinity, ammonia and DO were higher in the dry period. TSS, hardness and COD, on the other hand, were higher during the rainy season. The statistical analyses showed that Ca, K, Mg and Na are directly connected to the Chemical Oxygen Demand, which indicates a possibility of their input into the reservoir system by domestic sewage and agricultural run-offs. These statistical applications, thus, are also relevant in cases of environmental management and policy decision-making processes, to identify which factors should be further studied and/or modified to recover degraded or contaminated water bodies. Copyright © 2012 Elsevier B.V. All rights reserved.
Gait patterns for crime fighting: statistical evaluation
NASA Astrophysics Data System (ADS)
Sulovská, Kateřina; Bělašková, Silvie; Adámek, Milan
2013-10-01
The criminality is omnipresent during the human history. Modern technology brings novel opportunities for identification of a perpetrator. One of these opportunities is an analysis of video recordings, which may be taken during the crime itself or before/after the crime. The video analysis can be classed as identification analyses, respectively identification of a person via externals. The bipedal locomotion focuses on human movement on the basis of their anatomical-physiological features. Nowadays, the human gait is tested by many laboratories to learn whether the identification via bipedal locomotion is possible or not. The aim of our study is to use 2D components out of 3D data from the VICON Mocap system for deep statistical analyses. This paper introduces recent results of a fundamental study focused on various gait patterns during different conditions. The study contains data from 12 participants. Curves obtained from these measurements were sorted, averaged and statistically tested to estimate the stability and distinctiveness of this biometrics. Results show satisfactory distinctness of some chosen points, while some do not embody significant difference. However, results presented in this paper are of initial phase of further deeper and more exacting analyses of gait patterns under different conditions.
Statistical Selection of Biological Models for Genome-Wide Association Analyses.
Bi, Wenjian; Kang, Guolian; Pounds, Stanley B
2018-05-24
Genome-wide association studies have discovered many biologically important associations of genes with phenotypes. Typically, genome-wide association analyses formally test the association of each genetic feature (SNP, CNV, etc) with the phenotype of interest and summarize the results with multiplicity-adjusted p-values. However, very small p-values only provide evidence against the null hypothesis of no association without indicating which biological model best explains the observed data. Correctly identifying a specific biological model may improve the scientific interpretation and can be used to more effectively select and design a follow-up validation study. Thus, statistical methodology to identify the correct biological model for a particular genotype-phenotype association can be very useful to investigators. Here, we propose a general statistical method to summarize how accurately each of five biological models (null, additive, dominant, recessive, co-dominant) represents the data observed for each variant in a GWAS study. We show that the new method stringently controls the false discovery rate and asymptotically selects the correct biological model. Simulations of two-stage discovery-validation studies show that the new method has these properties and that its validation power is similar to or exceeds that of simple methods that use the same statistical model for all SNPs. Example analyses of three data sets also highlight these advantages of the new method. An R package is freely available at www.stjuderesearch.org/site/depts/biostats/maew. Copyright © 2018. Published by Elsevier Inc.
Students' attitudes towards learning statistics
NASA Astrophysics Data System (ADS)
Ghulami, Hassan Rahnaward; Hamid, Mohd Rashid Ab; Zakaria, Roslinazairimah
2015-05-01
Positive attitude towards learning is vital in order to master the core content of the subject matters under study. This is unexceptional in learning statistics course especially at the university level. Therefore, this study investigates the students' attitude towards learning statistics. Six variables or constructs have been identified such as affect, cognitive competence, value, difficulty, interest, and effort. The instrument used for the study is questionnaire that was adopted and adapted from the reliable instrument of Survey of Attitudes towards Statistics(SATS©). This study is conducted to engineering undergraduate students in one of the university in the East Coast of Malaysia. The respondents consist of students who were taking the applied statistics course from different faculties. The results are analysed in terms of descriptive analysis and it contributes to the descriptive understanding of students' attitude towards the teaching and learning process of statistics.
Methodological difficulties of conducting agroecological studies from a statistical perspective
USDA-ARS?s Scientific Manuscript database
Statistical methods for analysing agroecological data might not be able to help agroecologists to solve all of the current problems concerning crop and animal husbandry, but such methods could well help agroecologists to assess, tackle, and resolve several agroecological issues in a more reliable an...
Secondary Analysis of Qualitative Data.
ERIC Educational Resources Information Center
Turner, Paul D.
The reanalysis of data to answer the original research question with better statistical techniques or to answer new questions with old data is not uncommon in quantitative studies. Meta analysis and research syntheses have increased with the increase in research using similar statistical analyses, refinements of analytical techniques, and the…
Kuss, O
2015-03-30
Meta-analyses with rare events, especially those that include studies with no event in one ('single-zero') or even both ('double-zero') treatment arms, are still a statistical challenge. In the case of double-zero studies, researchers in general delete these studies or use continuity corrections to avoid them. A number of arguments against both options has been given, and statistical methods that use the information from double-zero studies without using continuity corrections have been proposed. In this paper, we collect them and compare them by simulation. This simulation study tries to mirror real-life situations as completely as possible by deriving true underlying parameters from empirical data on actually performed meta-analyses. It is shown that for each of the commonly encountered effect estimators valid statistical methods are available that use the information from double-zero studies without using continuity corrections. Interestingly, all of them are truly random effects models, and so also the current standard method for very sparse data as recommended from the Cochrane collaboration, the Yusuf-Peto odds ratio, can be improved on. For actual analysis, we recommend to use beta-binomial regression methods to arrive at summary estimates for the odds ratio, the relative risk, or the risk difference. Methods that ignore information from double-zero studies or use continuity corrections should no longer be used. We illustrate the situation with an example where the original analysis ignores 35 double-zero studies, and a superior analysis discovers a clinically relevant advantage of off-pump surgery in coronary artery bypass grafting. Copyright © 2014 John Wiley & Sons, Ltd.
Australasian Resuscitation In Sepsis Evaluation trial statistical analysis plan.
Delaney, Anthony; Peake, Sandra L; Bellomo, Rinaldo; Cameron, Peter; Holdgate, Anna; Howe, Belinda; Higgins, Alisa; Presneill, Jeffrey; Webb, Steve
2013-10-01
The Australasian Resuscitation In Sepsis Evaluation (ARISE) study is an international, multicentre, randomised, controlled trial designed to evaluate the effectiveness of early goal-directed therapy compared with standard care for patients presenting to the ED with severe sepsis. In keeping with current practice, and taking into considerations aspects of trial design and reporting specific to non-pharmacologic interventions, this document outlines the principles and methods for analysing and reporting the trial results. The document is prepared prior to completion of recruitment into the ARISE study, without knowledge of the results of the interim analysis conducted by the data safety and monitoring committee and prior to completion of the two related international studies. The statistical analysis plan was designed by the ARISE chief investigators, and reviewed and approved by the ARISE steering committee. The data collected by the research team as specified in the study protocol, and detailed in the study case report form were reviewed. Information related to baseline characteristics, characteristics of delivery of the trial interventions, details of resuscitation and other related therapies, and other relevant data are described with appropriate comparisons between groups. The primary, secondary and tertiary outcomes for the study are defined, with description of the planned statistical analyses. A statistical analysis plan was developed, along with a trial profile, mock-up tables and figures. A plan for presenting baseline characteristics, microbiological and antibiotic therapy, details of the interventions, processes of care and concomitant therapies, along with adverse events are described. The primary, secondary and tertiary outcomes are described along with identification of subgroups to be analysed. A statistical analysis plan for the ARISE study has been developed, and is available in the public domain, prior to the completion of recruitment into the study. This will minimise analytic bias and conforms to current best practice in conducting clinical trials. © 2013 Australasian College for Emergency Medicine and Australasian Society for Emergency Medicine.
Grey literature in meta-analyses.
Conn, Vicki S; Valentine, Jeffrey C; Cooper, Harris M; Rantz, Marilyn J
2003-01-01
In meta-analysis, researchers combine the results of individual studies to arrive at cumulative conclusions. Meta-analysts sometimes include "grey literature" in their evidential base, which includes unpublished studies and studies published outside widely available journals. Because grey literature is a source of data that might not employ peer review, critics have questioned the validity of its data and the results of meta-analyses that include it. To examine evidence regarding whether grey literature should be included in meta-analyses and strategies to manage grey literature in quantitative synthesis. This article reviews evidence on whether the results of studies published in peer-reviewed journals are representative of results from broader samplings of research on a topic as a rationale for inclusion of grey literature. Strategies to enhance access to grey literature are addressed. The most consistent and robust difference between published and grey literature is that published research is more likely to contain results that are statistically significant. Effect size estimates of published research are about one-third larger than those of unpublished studies. Unfunded and small sample studies are less likely to be published. Yet, importantly, methodological rigor does not differ between published and grey literature. Meta-analyses that exclude grey literature likely (a) over-represent studies with statistically significant findings, (b) inflate effect size estimates, and (c) provide less precise effect size estimates than meta-analyses including grey literature. Meta-analyses should include grey literature to fully reflect the existing evidential base and should assess the impact of methodological variations through moderator analysis.
Assessing the significance of pedobarographic signals using random field theory.
Pataky, Todd C
2008-08-07
Traditional pedobarographic statistical analyses are conducted over discrete regions. Recent studies have demonstrated that regionalization can corrupt pedobarographic field data through conflation when arbitrary dividing lines inappropriately delineate smooth field processes. An alternative is to register images such that homologous structures optimally overlap and then conduct statistical tests at each pixel to generate statistical parametric maps (SPMs). The significance of SPM processes may be assessed within the framework of random field theory (RFT). RFT is ideally suited to pedobarographic image analysis because its fundamental data unit is a lattice sampling of a smooth and continuous spatial field. To correct for the vast number of multiple comparisons inherent in such data, recent pedobarographic studies have employed a Bonferroni correction to retain a constant family-wise error rate. This approach unfortunately neglects the spatial correlation of neighbouring pixels, so provides an overly conservative (albeit valid) statistical threshold. RFT generally relaxes the threshold depending on field smoothness and on the geometry of the search area, but it also provides a framework for assigning p values to suprathreshold clusters based on their spatial extent. The current paper provides an overview of basic RFT concepts and uses simulated and experimental data to validate both RFT-relevant field smoothness estimations and RFT predictions regarding the topological characteristics of random pedobarographic fields. Finally, previously published experimental data are re-analysed using RFT inference procedures to demonstrate how RFT yields easily understandable statistical results that may be incorporated into routine clinical and laboratory analyses.
Family Early Literacy Practices Questionnaire: A Validation Study for a Spanish-Speaking Population
ERIC Educational Resources Information Center
Lewis, Kandia
2012-01-01
The purpose of the current study was to evaluate the psychometric validity of a Spanish translated version of a family involvement questionnaire (the FELP) using a mixed-methods design. Thus, statistical analyses (i.e., factor analysis, reliability analysis, and item analysis) and qualitative analyses (i.e., focus group data) were assessed.…
Statistical Data Analyses of Trace Chemical, Biochemical, and Physical Analytical Signatures
DOE Office of Scientific and Technical Information (OSTI.GOV)
Udey, Ruth Norma
Analytical and bioanalytical chemistry measurement results are most meaningful when interpreted using rigorous statistical treatments of the data. The same data set may provide many dimensions of information depending on the questions asked through the applied statistical methods. Three principal projects illustrated the wealth of information gained through the application of statistical data analyses to diverse problems.
Descriptive and inferential statistical methods used in burns research.
Al-Benna, Sammy; Al-Ajam, Yazan; Way, Benjamin; Steinstraesser, Lars
2010-05-01
Burns research articles utilise a variety of descriptive and inferential methods to present and analyse data. The aim of this study was to determine the descriptive methods (e.g. mean, median, SD, range, etc.) and survey the use of inferential methods (statistical tests) used in articles in the journal Burns. This study defined its population as all original articles published in the journal Burns in 2007. Letters to the editor, brief reports, reviews, and case reports were excluded. Study characteristics, use of descriptive statistics and the number and types of statistical methods employed were evaluated. Of the 51 articles analysed, 11(22%) were randomised controlled trials, 18(35%) were cohort studies, 11(22%) were case control studies and 11(22%) were case series. The study design and objectives were defined in all articles. All articles made use of continuous and descriptive data. Inferential statistics were used in 49(96%) articles. Data dispersion was calculated by standard deviation in 30(59%). Standard error of the mean was quoted in 19(37%). The statistical software product was named in 33(65%). Of the 49 articles that used inferential statistics, the tests were named in 47(96%). The 6 most common tests used (Student's t-test (53%), analysis of variance/co-variance (33%), chi(2) test (27%), Wilcoxon & Mann-Whitney tests (22%), Fisher's exact test (12%)) accounted for the majority (72%) of statistical methods employed. A specified significance level was named in 43(88%) and the exact significance levels were reported in 28(57%). Descriptive analysis and basic statistical techniques account for most of the statistical tests reported. This information should prove useful in deciding which tests should be emphasised in educating burn care professionals. These results highlight the need for burn care professionals to have a sound understanding of basic statistics, which is crucial in interpreting and reporting data. Advice should be sought from professionals in the fields of biostatistics and epidemiology when using more advanced statistical techniques. Copyright 2009 Elsevier Ltd and ISBI. All rights reserved.
ERIC Educational Resources Information Center
Brossart, Daniel F.; Parker, Richard I.; Olson, Elizabeth A.; Mahadevan, Lakshmi
2006-01-01
This study explored some practical issues for single-case researchers who rely on visual analysis of graphed data, but who also may consider supplemental use of promising statistical analysis techniques. The study sought to answer three major questions: (a) What is a typical range of effect sizes from these analytic techniques for data from…
ERIC Educational Resources Information Center
Dong, Nianbo; Spybrook, Jessaca; Kelcey, Ben
2016-01-01
The purpose of this study is to propose a general framework for power analyses to detect the moderator effects in two- and three-level cluster randomized trials (CRTs). The study specifically aims to: (1) develop the statistical formulations for calculating statistical power, minimum detectable effect size (MDES) and its confidence interval to…
Pejtersen, Jan Hyld; Burr, Hermann; Hannerz, Harald; Fishta, Alba; Hurwitz Eller, Nanna
2015-01-01
The present review deals with the relationship between occupational psychosocial factors and the incidence of ischemic heart disease (IHD) with special regard to the statistical power of the findings. This review with 4 inclusion criteria is an update of a 2009 review of which the first 3 criteria were included in the original review: (1) STUDY: a prospective or case-control study if exposure was not self-reported (prognostic studies excluded); (2) OUTCOME: definite IHD determined externally; (3) EXPOSURE: psychosocial factors at work (excluding shift work, trauma, violence or accidents, and social capital); and (4) Statistical power: acceptable to detect a 20% increased risk in IHD. Eleven new papers met the inclusion criteria 1-3; a total of 44 papers were evaluated regarding inclusion criteria 4. Of 169 statistical analyses, only 10 analyses in 2 papers had acceptable statistical power. The results of the 2 papers pointed in the same direction, namely that only the control dimension of job strain explained the excess risk for myocardial infarction for job strain. The large number of underpowered studies and the focus on psychosocial models, such as the job strain models, make it difficult to determine to what extent psychosocial factors at work are risk factors of IHD. There is a need for considering statistical power when planning studies.
Night shift work and breast cancer risk: what do the meta-analyses tell us?
Pahwa, Manisha; Labrèche, France; Demers, Paul A
2018-05-22
Objectives This paper aims to compare results, assess the quality, and discuss the implications of recently published meta-analyses of night shift work and breast cancer risk. Methods A comprehensive search was conducted for meta-analyses published from 2007-2017 that included at least one pooled effect size (ES) for breast cancer associated with any night shift work exposure metric and were accompanied by a systematic literature review. Pooled ES from each meta-analysis were ascertained with a focus on ever/never exposure associations. Assessments of heterogeneity and publication bias were also extracted. The AMSTAR 2 checklist was used to evaluate quality. Results Seven meta-analyses, published from 2013-2016, collectively included 30 cohort and case-control studies spanning 1996-2016. Five meta-analyses reported pooled ES for ever/never night shift work exposure; these ranged from 0.99 [95% confidence interval (CI) 0.95-1.03, N=10 cohort studies) to 1.40 (95% CI 1.13-1.73, N=9 high quality studies). Estimates for duration, frequency, and cumulative night shift work exposure were scant and mostly not statistically significant. Meta-analyses of cohort, Asian, and more fully-adjusted studies generally resulted in lower pooled ES than case-control, European, American, or minimally-adjusted studies. Most reported statistically significant between-study heterogeneity. Publication bias was not evident in any of the meta-analyses. Only one meta-analysis was strong in critical quality domains. Conclusions Fairly consistent elevated pooled ES were found for ever/never night shift work and breast cancer risk, but results for other shift work exposure metrics were inconclusive. Future evaluations of shift work should incorporate high quality meta-analyses that better appraise individual study quality.
2011-01-01
Background Cochrane systematic reviews collate and summarise studies of the effects of healthcare interventions. The characteristics of these reviews and the meta-analyses and individual studies they contain provide insights into the nature of healthcare research and important context for the development of relevant statistical and other methods. Methods We classified every meta-analysis with at least two studies in every review in the January 2008 issue of the Cochrane Database of Systematic Reviews (CDSR) according to the medical specialty, the types of interventions being compared and the type of outcome. We provide descriptive statistics for numbers of meta-analyses, numbers of component studies and sample sizes of component studies, broken down by these categories. Results We included 2321 reviews containing 22,453 meta-analyses, which themselves consist of data from 112,600 individual studies (which may appear in more than one meta-analysis). Meta-analyses in the areas of gynaecology, pregnancy and childbirth (21%), mental health (13%) and respiratory diseases (13%) are well represented in the CDSR. Most meta-analyses address drugs, either with a control or placebo group (37%) or in a comparison with another drug (25%). The median number of meta-analyses per review is six (inter-quartile range 3 to 12). The median number of studies included in the meta-analyses with at least two studies is three (inter-quartile range 2 to 6). Sample sizes of individual studies range from 2 to 1,242,071, with a median of 91 participants. Discussion It is clear that the numbers of studies eligible for meta-analyses are typically very small for all medical areas, outcomes and interventions covered by Cochrane reviews. This highlights the particular importance of suitable methods for the meta-analysis of small data sets. There was little variation in number of studies per meta-analysis across medical areas, across outcome data types or across types of interventions being compared. PMID:22114982
Most analyses of daily time series epidemiology data relate mortality or morbidity counts to PM and other air pollutants by means of single-outcome regression models using multiple predictors, without taking into account the complex statistical structure of the predictor variable...
Testosterone replacement therapy and the heart: friend, foe or bystander?
Canfield, Steven; Wang, Run
2016-01-01
The role of testosterone therapy (TTh) in cardiovascular disease (CVD) outcomes is still controversial, and it seems will remain inconclusive for the moment. An extensive body of literature has investigated the association of endogenous testosterone and use of TTh with CVD events including several meta-analyses. In some instances, a number of studies reported beneficial effects of TTh on CVD events and in other instances the body of literature reported detrimental effects or no effects at all. Yet, no review article has scrutinized this body of literature using the magnitude of associations and statistical significance reported from this relationship. We critically reviewed the previous and emerging body of literature that investigated the association of endogenous testosterone and use of TTh with CVD events (only fatal and nonfatal). These studies were divided into three groups, “beneficial (friendly use)”, “detrimental (foe)” and “no effects at all (bystander)”, based on their magnitude of associations and statistical significance from original research studies and meta-analyses of epidemiological studies and of randomized controlled trials (RCT’s). In this review article, the studies reporting a significant association of high levels of testosterone with a reduced risk of CVD events in original prospective studies and meta-analyses of cross-sectional and prospective studies seems to be more consistent. However, the number of meta-analyses of RCT’s does not provide a clear picture after we divided it into the beneficial, detrimental or no effects all groups using their magnitudes of association and statistical significance. From this review, we suggest that we need a study or number of studies that have the adequate power, epidemiological, and clinical data to provide a definitive conclusion on whether the effect of TTh on the natural history of CVD is real or not. PMID:28078222
Testosterone replacement therapy and the heart: friend, foe or bystander?
Lopez, David S; Canfield, Steven; Wang, Run
2016-12-01
The role of testosterone therapy (TTh) in cardiovascular disease (CVD) outcomes is still controversial, and it seems will remain inconclusive for the moment. An extensive body of literature has investigated the association of endogenous testosterone and use of TTh with CVD events including several meta-analyses. In some instances, a number of studies reported beneficial effects of TTh on CVD events and in other instances the body of literature reported detrimental effects or no effects at all. Yet, no review article has scrutinized this body of literature using the magnitude of associations and statistical significance reported from this relationship. We critically reviewed the previous and emerging body of literature that investigated the association of endogenous testosterone and use of TTh with CVD events (only fatal and nonfatal). These studies were divided into three groups, "beneficial (friendly use)", "detrimental (foe)" and "no effects at all (bystander)", based on their magnitude of associations and statistical significance from original research studies and meta-analyses of epidemiological studies and of randomized controlled trials (RCT's). In this review article, the studies reporting a significant association of high levels of testosterone with a reduced risk of CVD events in original prospective studies and meta-analyses of cross-sectional and prospective studies seems to be more consistent. However, the number of meta-analyses of RCT's does not provide a clear picture after we divided it into the beneficial, detrimental or no effects all groups using their magnitudes of association and statistical significance. From this review, we suggest that we need a study or number of studies that have the adequate power, epidemiological, and clinical data to provide a definitive conclusion on whether the effect of TTh on the natural history of CVD is real or not.
SOCR Analyses – an Instructional Java Web-based Statistical Analysis Toolkit
Chu, Annie; Cui, Jenny; Dinov, Ivo D.
2011-01-01
The Statistical Online Computational Resource (SOCR) designs web-based tools for educational use in a variety of undergraduate courses (Dinov 2006). Several studies have demonstrated that these resources significantly improve students' motivation and learning experiences (Dinov et al. 2008). SOCR Analyses is a new component that concentrates on data modeling and analysis using parametric and non-parametric techniques supported with graphical model diagnostics. Currently implemented analyses include commonly used models in undergraduate statistics courses like linear models (Simple Linear Regression, Multiple Linear Regression, One-Way and Two-Way ANOVA). In addition, we implemented tests for sample comparisons, such as t-test in the parametric category; and Wilcoxon rank sum test, Kruskal-Wallis test, Friedman's test, in the non-parametric category. SOCR Analyses also include several hypothesis test models, such as Contingency tables, Friedman's test and Fisher's exact test. The code itself is open source (http://socr.googlecode.com/), hoping to contribute to the efforts of the statistical computing community. The code includes functionality for each specific analysis model and it has general utilities that can be applied in various statistical computing tasks. For example, concrete methods with API (Application Programming Interface) have been implemented in statistical summary, least square solutions of general linear models, rank calculations, etc. HTML interfaces, tutorials, source code, activities, and data are freely available via the web (www.SOCR.ucla.edu). Code examples for developers and demos for educators are provided on the SOCR Wiki website. In this article, the pedagogical utilization of the SOCR Analyses is discussed, as well as the underlying design framework. As the SOCR project is on-going and more functions and tools are being added to it, these resources are constantly improved. The reader is strongly encouraged to check the SOCR site for most updated information and newly added models. PMID:21546994
Parent and Friend Social Support and Adolescent Hope.
Mahon, Noreen E; Yarcheski, Adela
2017-04-01
The purpose of this study was to conduct two meta-analyses. The first examined social support from parents in relation to adolescent hope, and the second examined social support from friends in relation to adolescent hope. Using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for the literature reviewed, nine published studies or doctoral dissertations completed between 1990 and 2014 met the inclusion criteria. Using meta-analytic techniques and the mean weighted r statistic, the results indicated that social support from friends had a stronger mean effect size (ES = .31) than social support from parents (ES = .21); there was a statistically significant difference between the two ESs. Two of the four moderators for the parent social support-adolescent hope relationship were statistically significant. They were quality score and health status. Implications for school nurses and nurses in all settings are addressed, and conclusions are drawn based on the findings.
Tomlinson, Alan; Hair, Mario; McFadyen, Angus
2013-10-01
Dry eye is a multifactorial disease which would require a broad spectrum of test measures in the monitoring of its treatment and diagnosis. However, studies have typically reported improvements in individual measures with treatment. Alternative approaches involve multiple, combined outcomes being assessed by different statistical analyses. In order to assess the effect of various statistical approaches to the use of single and combined test measures in dry eye, this review reanalyzed measures from two previous studies (osmolarity, evaporation, tear turnover rate, and lipid film quality). These analyses assessed the measures as single variables within groups, pre- and post-intervention with a lubricant supplement, by creating combinations of these variables and by validating these combinations with the combined sample of data from all groups of dry eye subjects. The effectiveness of single measures and combinations in diagnosis of dry eye was also considered. Copyright © 2013. Published by Elsevier Inc.
The intervals method: a new approach to analyse finite element outputs using multivariate statistics
De Esteban-Trivigno, Soledad; Püschel, Thomas A.; Fortuny, Josep
2017-01-01
Background In this paper, we propose a new method, named the intervals’ method, to analyse data from finite element models in a comparative multivariate framework. As a case study, several armadillo mandibles are analysed, showing that the proposed method is useful to distinguish and characterise biomechanical differences related to diet/ecomorphology. Methods The intervals’ method consists of generating a set of variables, each one defined by an interval of stress values. Each variable is expressed as a percentage of the area of the mandible occupied by those stress values. Afterwards these newly generated variables can be analysed using multivariate methods. Results Applying this novel method to the biological case study of whether armadillo mandibles differ according to dietary groups, we show that the intervals’ method is a powerful tool to characterize biomechanical performance and how this relates to different diets. This allows us to positively discriminate between specialist and generalist species. Discussion We show that the proposed approach is a useful methodology not affected by the characteristics of the finite element mesh. Additionally, the positive discriminating results obtained when analysing a difficult case study suggest that the proposed method could be a very useful tool for comparative studies in finite element analysis using multivariate statistical approaches. PMID:29043107
2016-11-15
participants who were followed for the development of back pain for an average of 3.9 years. Methods. Descriptive statistics and longitudinal...health, military personnel, occupational health, outcome assessment, statistics, survey methodology . Level of Evidence: 3 Spine 2016;41:1754–1763ack...based on the National Health and Nutrition Examination Survey.21 Statistical Analysis Descriptive and univariate analyses compared character- istics
STRengthening analytical thinking for observational studies: the STRATOS initiative.
Sauerbrei, Willi; Abrahamowicz, Michal; Altman, Douglas G; le Cessie, Saskia; Carpenter, James
2014-12-30
The validity and practical utility of observational medical research depends critically on good study design, excellent data quality, appropriate statistical methods and accurate interpretation of results. Statistical methodology has seen substantial development in recent times. Unfortunately, many of these methodological developments are ignored in practice. Consequently, design and analysis of observational studies often exhibit serious weaknesses. The lack of guidance on vital practical issues discourages many applied researchers from using more sophisticated and possibly more appropriate methods when analyzing observational studies. Furthermore, many analyses are conducted by researchers with a relatively weak statistical background and limited experience in using statistical methodology and software. Consequently, even 'standard' analyses reported in the medical literature are often flawed, casting doubt on their results and conclusions. An efficient way to help researchers to keep up with recent methodological developments is to develop guidance documents that are spread to the research community at large. These observations led to the initiation of the strengthening analytical thinking for observational studies (STRATOS) initiative, a large collaboration of experts in many different areas of biostatistical research. The objective of STRATOS is to provide accessible and accurate guidance in the design and analysis of observational studies. The guidance is intended for applied statisticians and other data analysts with varying levels of statistical education, experience and interests. In this article, we introduce the STRATOS initiative and its main aims, present the need for guidance documents and outline the planned approach and progress so far. We encourage other biostatisticians to become involved. © 2014 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd.
Shadish, William R; Hedges, Larry V; Pustejovsky, James E
2014-04-01
This article presents a d-statistic for single-case designs that is in the same metric as the d-statistic used in between-subjects designs such as randomized experiments and offers some reasons why such a statistic would be useful in SCD research. The d has a formal statistical development, is accompanied by appropriate power analyses, and can be estimated using user-friendly SPSS macros. We discuss both advantages and disadvantages of d compared to other approaches such as previous d-statistics, overlap statistics, and multilevel modeling. It requires at least three cases for computation and assumes normally distributed outcomes and stationarity, assumptions that are discussed in some detail. We also show how to test these assumptions. The core of the article then demonstrates in depth how to compute d for one study, including estimation of the autocorrelation and the ratio of between case variance to total variance (between case plus within case variance), how to compute power using a macro, and how to use the d to conduct a meta-analysis of studies using single-case designs in the free program R, including syntax in an appendix. This syntax includes how to read data, compute fixed and random effect average effect sizes, prepare a forest plot and a cumulative meta-analysis, estimate various influence statistics to identify studies contributing to heterogeneity and effect size, and do various kinds of publication bias analyses. This d may prove useful for both the analysis and meta-analysis of data from SCDs. Copyright © 2013 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.
Mercer, Theresa G; Frostick, Lynne E; Walmsley, Anthony D
2011-10-15
This paper presents a statistical technique that can be applied to environmental chemistry data where missing values and limit of detection levels prevent the application of statistics. A working example is taken from an environmental leaching study that was set up to determine if there were significant differences in levels of leached arsenic (As), chromium (Cr) and copper (Cu) between lysimeters containing preservative treated wood waste and those containing untreated wood. Fourteen lysimeters were setup and left in natural conditions for 21 weeks. The resultant leachate was analysed by ICP-OES to determine the As, Cr and Cu concentrations. However, due to the variation inherent in each lysimeter combined with the limits of detection offered by ICP-OES, the collected quantitative data was somewhat incomplete. Initial data analysis was hampered by the number of 'missing values' in the data. To recover the dataset, the statistical tool of Statistical Multiple Imputation (SMI) was applied, and the data was re-analysed successfully. It was demonstrated that using SMI did not affect the variance in the data, but facilitated analysis of the complete dataset. Copyright © 2011 Elsevier B.V. All rights reserved.
Early Warning Signs of Suicide in Service Members Who Engage in Unauthorized Acts of Violence
2016-06-01
observable to military law enforcement personnel. Statistical analyses tested for differences in warning signs between cases of suicide, violence, or...indicators, (2) Behavioral Change indicators, (3) Social indicators, and (4) Occupational indicators. Statistical analyses were conducted to test for...6 Coding _________________________________________________________________ 7 Statistical
Body Weight Reducing Effect of Oral Boric Acid Intake
Aysan, Erhan; Sahin, Fikrettin; Telci, Dilek; Yalvac, Mehmet Emir; Emre, Sinem Hocaoglu; Karaca, Cetin; Muslumanoglu, Mahmut
2011-01-01
Background: Boric acid is widely used in biology, but its body weight reducing effect is not researched. Methods: Twenty mice were divided into two equal groups. Control group mice drank standard tap water, but study group mice drank 0.28mg/250ml boric acid added tap water over five days. Total body weight changes, major organ histopathology, blood biochemistry, urine and feces analyses were compared. Results: Study group mice lost body weight mean 28.1% but in control group no weight loss and also weight gained mean 0.09% (p<0.001). Total drinking water and urine outputs were not statistically different. Cholesterol, LDL, AST, ALT, LDH, amylase and urobilinogen levels were statistically significantly high in the study group. Other variables were not statistically different. No histopathologic differences were detected in evaluations of all resected major organs. Conclusion: Low dose oral boric acid intake cause serious body weight reduction. Blood and urine analyses support high glucose, lipid and middle protein catabolisms, but the mechanism is unclear. PMID:22135611
Body weight reducing effect of oral boric acid intake.
Aysan, Erhan; Sahin, Fikrettin; Telci, Dilek; Yalvac, Mehmet Emir; Emre, Sinem Hocaoglu; Karaca, Cetin; Muslumanoglu, Mahmut
2011-01-01
Boric acid is widely used in biology, but its body weight reducing effect is not researched. Twenty mice were divided into two equal groups. Control group mice drank standard tap water, but study group mice drank 0.28mg/250ml boric acid added tap water over five days. Total body weight changes, major organ histopathology, blood biochemistry, urine and feces analyses were compared. Study group mice lost body weight mean 28.1% but in control group no weight loss and also weight gained mean 0.09% (p<0.001). Total drinking water and urine outputs were not statistically different. Cholesterol, LDL, AST, ALT, LDH, amylase and urobilinogen levels were statistically significantly high in the study group. Other variables were not statistically different. No histopathologic differences were detected in evaluations of all resected major organs. Low dose oral boric acid intake cause serious body weight reduction. Blood and urine analyses support high glucose, lipid and middle protein catabolisms, but the mechanism is unclear.
Ratio index variables or ANCOVA? Fisher's cats revisited.
Tu, Yu-Kang; Law, Graham R; Ellison, George T H; Gilthorpe, Mark S
2010-01-01
Over 60 years ago Ronald Fisher demonstrated a number of potential pitfalls with statistical analyses using ratio variables. Nonetheless, these pitfalls are largely overlooked in contemporary clinical and epidemiological research, which routinely uses ratio variables in statistical analyses. This article aims to demonstrate how very different findings can be generated as a result of less than perfect correlations among the data used to generate ratio variables. These imperfect correlations result from measurement error and random biological variation. While the former can often be reduced by improvements in measurement, random biological variation is difficult to estimate and eliminate in observational studies. Moreover, wherever the underlying biological relationships among epidemiological variables are unclear, and hence the choice of statistical model is also unclear, the different findings generated by different analytical strategies can lead to contradictory conclusions. Caution is therefore required when interpreting analyses of ratio variables whenever the underlying biological relationships among the variables involved are unspecified or unclear. (c) 2009 John Wiley & Sons, Ltd.
Chapter C. The Loma Prieta, California, Earthquake of October 17, 1989 - Building Structures
Çelebi, Mehmet
1998-01-01
Several approaches are used to assess the performance of the built environment following an earthquake -- preliminary damage surveys conducted by professionals, detailed studies of individual structures, and statistical analyses of groups of structures. Reports of damage that are issued by many organizations immediately following an earthquake play a key role in directing subsequent detailed investigations. Detailed studies of individual structures and statistical analyses of groups of structures may be motivated by particularly good or bad performance during an earthquake. Beyond this, practicing engineers typically perform stress analyses to assess the performance of a particular structure to vibrational levels experienced during an earthquake. The levels may be determined from recorded or estimated ground motions; actual levels usually differ from design levels. If a structure has seismic instrumentation to record response data, the estimated and recorded response and behavior of the structure can be compared.
ERIC Educational Resources Information Center
Spybrook, Jessaca; Hedges, Larry; Borenstein, Michael
2014-01-01
Research designs in which clusters are the unit of randomization are quite common in the social sciences. Given the multilevel nature of these studies, the power analyses for these studies are more complex than in a simple individually randomized trial. Tools are now available to help researchers conduct power analyses for cluster randomized…
The Economic Cost of Homosexuality: Multilevel Analyses
ERIC Educational Resources Information Center
Baumle, Amanda K.; Poston, Dudley, Jr.
2011-01-01
This article builds on earlier studies that have examined "the economic cost of homosexuality," by using data from the 2000 U.S. Census and by employing multilevel analyses. Our findings indicate that partnered gay men experience a 12.5 percent earnings penalty compared to married heterosexual men, and a statistically insignificant earnings…
STRengthening Analytical Thinking for Observational Studies: the STRATOS initiative
Sauerbrei, Willi; Abrahamowicz, Michal; Altman, Douglas G; le Cessie, Saskia; Carpenter, James
2014-01-01
The validity and practical utility of observational medical research depends critically on good study design, excellent data quality, appropriate statistical methods and accurate interpretation of results. Statistical methodology has seen substantial development in recent times. Unfortunately, many of these methodological developments are ignored in practice. Consequently, design and analysis of observational studies often exhibit serious weaknesses. The lack of guidance on vital practical issues discourages many applied researchers from using more sophisticated and possibly more appropriate methods when analyzing observational studies. Furthermore, many analyses are conducted by researchers with a relatively weak statistical background and limited experience in using statistical methodology and software. Consequently, even ‘standard’ analyses reported in the medical literature are often flawed, casting doubt on their results and conclusions. An efficient way to help researchers to keep up with recent methodological developments is to develop guidance documents that are spread to the research community at large. These observations led to the initiation of the strengthening analytical thinking for observational studies (STRATOS) initiative, a large collaboration of experts in many different areas of biostatistical research. The objective of STRATOS is to provide accessible and accurate guidance in the design and analysis of observational studies. The guidance is intended for applied statisticians and other data analysts with varying levels of statistical education, experience and interests. In this article, we introduce the STRATOS initiative and its main aims, present the need for guidance documents and outline the planned approach and progress so far. We encourage other biostatisticians to become involved. PMID:25074480
Exploring Foundation Concepts in Introductory Statistics Using Dynamic Data Points
ERIC Educational Resources Information Center
Ekol, George
2015-01-01
This paper analyses introductory statistics students' verbal and gestural expressions as they interacted with a dynamic sketch (DS) designed using "Sketchpad" software. The DS involved numeric data points built on the number line whose values changed as the points were dragged along the number line. The study is framed on aggregate…
Trends in study design and the statistical methods employed in a leading general medicine journal.
Gosho, M; Sato, Y; Nagashima, K; Takahashi, S
2018-02-01
Study design and statistical methods have become core components of medical research, and the methodology has become more multifaceted and complicated over time. The study of the comprehensive details and current trends of study design and statistical methods is required to support the future implementation of well-planned clinical studies providing information about evidence-based medicine. Our purpose was to illustrate study design and statistical methods employed in recent medical literature. This was an extension study of Sato et al. (N Engl J Med 2017; 376: 1086-1087), which reviewed 238 articles published in 2015 in the New England Journal of Medicine (NEJM) and briefly summarized the statistical methods employed in NEJM. Using the same database, we performed a new investigation of the detailed trends in study design and individual statistical methods that were not reported in the Sato study. Due to the CONSORT statement, prespecification and justification of sample size are obligatory in planning intervention studies. Although standard survival methods (eg Kaplan-Meier estimator and Cox regression model) were most frequently applied, the Gray test and Fine-Gray proportional hazard model for considering competing risks were sometimes used for a more valid statistical inference. With respect to handling missing data, model-based methods, which are valid for missing-at-random data, were more frequently used than single imputation methods. These methods are not recommended as a primary analysis, but they have been applied in many clinical trials. Group sequential design with interim analyses was one of the standard designs, and novel design, such as adaptive dose selection and sample size re-estimation, was sometimes employed in NEJM. Model-based approaches for handling missing data should replace single imputation methods for primary analysis in the light of the information found in some publications. Use of adaptive design with interim analyses is increasing after the presentation of the FDA guidance for adaptive design. © 2017 John Wiley & Sons Ltd.
Using R-Project for Free Statistical Analysis in Extension Research
ERIC Educational Resources Information Center
Mangiafico, Salvatore S.
2013-01-01
One option for Extension professionals wishing to use free statistical software is to use online calculators, which are useful for common, simple analyses. A second option is to use a free computing environment capable of performing statistical analyses, like R-project. R-project is free, cross-platform, powerful, and respected, but may be…
Impact of ontology evolution on functional analyses.
Groß, Anika; Hartung, Michael; Prüfer, Kay; Kelso, Janet; Rahm, Erhard
2012-10-15
Ontologies are used in the annotation and analysis of biological data. As knowledge accumulates, ontologies and annotation undergo constant modifications to reflect this new knowledge. These modifications may influence the results of statistical applications such as functional enrichment analyses that describe experimental data in terms of ontological groupings. Here, we investigate to what degree modifications of the Gene Ontology (GO) impact these statistical analyses for both experimental and simulated data. The analysis is based on new measures for the stability of result sets and considers different ontology and annotation changes. Our results show that past changes in the GO are non-uniformly distributed over different branches of the ontology. Considering the semantic relatedness of significant categories in analysis results allows a more realistic stability assessment for functional enrichment studies. We observe that the results of term-enrichment analyses tend to be surprisingly stable despite changes in ontology and annotation.
An Exploratory Data Analysis System for Support in Medical Decision-Making
Copeland, J. A.; Hamel, B.; Bourne, J. R.
1979-01-01
An experimental system was developed to allow retrieval and analysis of data collected during a study of neurobehavioral correlates of renal disease. After retrieving data organized in a relational data base, simple bivariate statistics of parametric and nonparametric nature could be conducted. An “exploratory” mode in which the system provided guidance in selection of appropriate statistical analyses was also available to the user. The system traversed a decision tree using the inherent qualities of the data (e.g., the identity and number of patients, tests, and time epochs) to search for the appropriate analyses to employ.
Statistical study of air pollutant concentrations via generalized gamma distribution
DOE Office of Scientific and Technical Information (OSTI.GOV)
Marani, A.; Lavagnini, I.; Buttazzoni, C.
1986-11-01
This paper deals with modeling observed frequency distributions of air quality data measured in the area of Venice, Italy. The paper discusses the application of the generalized gamma distribution (ggd) which has not been commonly applied to air quality data notwithstanding the fact that it embodies most distribution models used for air quality analyses. The approach yields important simplifications for statistical analyses. A comparison among the ggd and other relevant models (standard gamma, Weibull, lognormal), carried out on daily sulfur dioxide concentrations in the area of Venice underlines the efficiency of ggd models in portraying experimental data.
Low statistical power in biomedical science: a review of three human research domains.
Dumas-Mallet, Estelle; Button, Katherine S; Boraud, Thomas; Gonon, Francois; Munafò, Marcus R
2017-02-01
Studies with low statistical power increase the likelihood that a statistically significant finding represents a false positive result. We conducted a review of meta-analyses of studies investigating the association of biological, environmental or cognitive parameters with neurological, psychiatric and somatic diseases, excluding treatment studies, in order to estimate the average statistical power across these domains. Taking the effect size indicated by a meta-analysis as the best estimate of the likely true effect size, and assuming a threshold for declaring statistical significance of 5%, we found that approximately 50% of studies have statistical power in the 0-10% or 11-20% range, well below the minimum of 80% that is often considered conventional. Studies with low statistical power appear to be common in the biomedical sciences, at least in the specific subject areas captured by our search strategy. However, we also observe evidence that this depends in part on research methodology, with candidate gene studies showing very low average power and studies using cognitive/behavioural measures showing high average power. This warrants further investigation.
Low statistical power in biomedical science: a review of three human research domains
Dumas-Mallet, Estelle; Button, Katherine S.; Boraud, Thomas; Gonon, Francois
2017-01-01
Studies with low statistical power increase the likelihood that a statistically significant finding represents a false positive result. We conducted a review of meta-analyses of studies investigating the association of biological, environmental or cognitive parameters with neurological, psychiatric and somatic diseases, excluding treatment studies, in order to estimate the average statistical power across these domains. Taking the effect size indicated by a meta-analysis as the best estimate of the likely true effect size, and assuming a threshold for declaring statistical significance of 5%, we found that approximately 50% of studies have statistical power in the 0–10% or 11–20% range, well below the minimum of 80% that is often considered conventional. Studies with low statistical power appear to be common in the biomedical sciences, at least in the specific subject areas captured by our search strategy. However, we also observe evidence that this depends in part on research methodology, with candidate gene studies showing very low average power and studies using cognitive/behavioural measures showing high average power. This warrants further investigation. PMID:28386409
Shitara, Kohei; Matsuo, Keitaro; Oze, Isao; Mizota, Ayako; Kondo, Chihiro; Nomura, Motoo; Yokota, Tomoya; Takahari, Daisuke; Ura, Takashi; Muro, Kei
2011-08-01
We performed a systematic review and meta-analysis to determine the impact of neutropenia or leukopenia experienced during chemotherapy on survival. Eligible studies included prospective or retrospective analyses that evaluated neutropenia or leukopenia as a prognostic factor for overall survival or disease-free survival. Statistical analyses were conducted to calculate a summary hazard ratio and 95% confidence interval (CI) using random-effects or fixed-effects models based on the heterogeneity of the included studies. Thirteen trials were selected for the meta-analysis, with a total of 9,528 patients. The hazard ratio of death was 0.69 (95% CI, 0.64-0.75) for patients with higher-grade neutropenia or leukopenia compared to patients with lower-grade or lack of cytopenia. Our analysis was also stratified by statistical method (any statistical method to decrease lead-time bias; time-varying analysis or landmark analysis), but no differences were observed. Our results indicate that neutropenia or leukopenia experienced during chemotherapy is associated with improved survival in patients with advanced cancer or hematological malignancies undergoing chemotherapy. Future prospective analyses designed to investigate the potential impact of chemotherapy dose adjustment coupled with monitoring of neutropenia or leukopenia on survival are warranted.
Statistical issues on the analysis of change in follow-up studies in dental research.
Blance, Andrew; Tu, Yu-Kang; Baelum, Vibeke; Gilthorpe, Mark S
2007-12-01
To provide an overview to the problems in study design and associated analyses of follow-up studies in dental research, particularly addressing three issues: treatment-baselineinteractions; statistical power; and nonrandomization. Our previous work has shown that many studies purport an interacion between change (from baseline) and baseline values, which is often based on inappropriate statistical analyses. A priori power calculations are essential for randomized controlled trials (RCTs), but in the pre-test/post-test RCT design it is not well known to dental researchers that the choice of statistical method affects power, and that power is affected by treatment-baseline interactions. A common (good) practice in the analysis of RCT data is to adjust for baseline outcome values using ancova, thereby increasing statistical power. However, an important requirement for ancova is there to be no interaction between the groups and baseline outcome (i.e. effective randomization); the patient-selection process should not cause differences in mean baseline values across groups. This assumption is often violated for nonrandomized (observational) studies and the use of ancova is thus problematic, potentially giving biased estimates, invoking Lord's paradox and leading to difficulties in the interpretation of results. Baseline interaction issues can be overcome by use of statistical methods; not widely practiced in dental research: Oldham's method and multilevel modelling; the latter is preferred for its greater flexibility to deal with more than one follow-up occasion as well as additional covariates To illustrate these three key issues, hypothetical examples are considered from the fields of periodontology, orthodontics, and oral implantology. Caution needs to be exercised when considering the design and analysis of follow-up studies. ancova is generally inappropriate for nonrandomized studies and causal inferences from observational data should be avoided.
Borrowing of strength and study weights in multivariate and network meta-analysis.
Jackson, Dan; White, Ian R; Price, Malcolm; Copas, John; Riley, Richard D
2017-12-01
Multivariate and network meta-analysis have the potential for the estimated mean of one effect to borrow strength from the data on other effects of interest. The extent of this borrowing of strength is usually assessed informally. We present new mathematical definitions of 'borrowing of strength'. Our main proposal is based on a decomposition of the score statistic, which we show can be interpreted as comparing the precision of estimates from the multivariate and univariate models. Our definition of borrowing of strength therefore emulates the usual informal assessment. We also derive a method for calculating study weights, which we embed into the same framework as our borrowing of strength statistics, so that percentage study weights can accompany the results from multivariate and network meta-analyses as they do in conventional univariate meta-analyses. Our proposals are illustrated using three meta-analyses involving correlated effects for multiple outcomes, multiple risk factor associations and multiple treatments (network meta-analysis).
Borrowing of strength and study weights in multivariate and network meta-analysis
Jackson, Dan; White, Ian R; Price, Malcolm; Copas, John; Riley, Richard D
2016-01-01
Multivariate and network meta-analysis have the potential for the estimated mean of one effect to borrow strength from the data on other effects of interest. The extent of this borrowing of strength is usually assessed informally. We present new mathematical definitions of ‘borrowing of strength’. Our main proposal is based on a decomposition of the score statistic, which we show can be interpreted as comparing the precision of estimates from the multivariate and univariate models. Our definition of borrowing of strength therefore emulates the usual informal assessment. We also derive a method for calculating study weights, which we embed into the same framework as our borrowing of strength statistics, so that percentage study weights can accompany the results from multivariate and network meta-analyses as they do in conventional univariate meta-analyses. Our proposals are illustrated using three meta-analyses involving correlated effects for multiple outcomes, multiple risk factor associations and multiple treatments (network meta-analysis). PMID:26546254
NASA Astrophysics Data System (ADS)
Emoto, K.; Saito, T.; Shiomi, K.
2017-12-01
Short-period (<1 s) seismograms are strongly affected by small-scale (<10 km) heterogeneities in the lithosphere. In general, short-period seismograms are analysed based on the statistical method by considering the interaction between seismic waves and randomly distributed small-scale heterogeneities. Statistical properties of the random heterogeneities have been estimated by analysing short-period seismograms. However, generally, the small-scale random heterogeneity is not taken into account for the modelling of long-period (>2 s) seismograms. We found that the energy of the coda of long-period seismograms shows a spatially flat distribution. This phenomenon is well known in short-period seismograms and results from the scattering by small-scale heterogeneities. We estimate the statistical parameters that characterize the small-scale random heterogeneity by modelling the spatiotemporal energy distribution of long-period seismograms. We analyse three moderate-size earthquakes that occurred in southwest Japan. We calculate the spatial distribution of the energy density recorded by a dense seismograph network in Japan at the period bands of 8-16 s, 4-8 s and 2-4 s and model them by using 3-D finite difference (FD) simulations. Compared to conventional methods based on statistical theories, we can calculate more realistic synthetics by using the FD simulation. It is not necessary to assume a uniform background velocity, body or surface waves and scattering properties considered in general scattering theories. By taking the ratio of the energy of the coda area to that of the entire area, we can separately estimate the scattering and the intrinsic absorption effects. Our result reveals the spectrum of the random inhomogeneity in a wide wavenumber range including the intensity around the corner wavenumber as P(m) = 8πε2a3/(1 + a2m2)2, where ε = 0.05 and a = 3.1 km, even though past studies analysing higher-frequency records could not detect the corner. Finally, we estimate the intrinsic attenuation by modelling the decay rate of the energy. The method proposed in this study is suitable for quantifying the statistical properties of long-wavelength subsurface random inhomogeneity, which leads the way to characterizing a wider wavenumber range of spectra, including the corner wavenumber.
Orphan therapies: making best use of postmarket data.
Maro, Judith C; Brown, Jeffrey S; Dal Pan, Gerald J; Li, Lingling
2014-08-01
Postmarket surveillance of the comparative safety and efficacy of orphan therapeutics is challenging, particularly when multiple therapeutics are licensed for the same orphan indication. To make best use of product-specific registry data collected to fulfill regulatory requirements, we propose the creation of a distributed electronic health data network among registries. Such a network could support sequential statistical analyses designed to detect early warnings of excess risks. We use a simulated example to explore the circumstances under which a distributed network may prove advantageous. We perform sample size calculations for sequential and non-sequential statistical studies aimed at comparing the incidence of hepatotoxicity following initiation of two newly licensed therapies for homozygous familial hypercholesterolemia. We calculate the sample size savings ratio, or the proportion of sample size saved if one conducted a sequential study as compared to a non-sequential study. Then, using models to describe the adoption and utilization of these therapies, we simulate when these sample sizes are attainable in calendar years. We then calculate the analytic calendar time savings ratio, analogous to the sample size savings ratio. We repeat these analyses for numerous scenarios. Sequential analyses detect effect sizes earlier or at the same time as non-sequential analyses. The most substantial potential savings occur when the market share is more imbalanced (i.e., 90% for therapy A) and the effect size is closest to the null hypothesis. However, due to low exposure prevalence, these savings are difficult to realize within the 30-year time frame of this simulation for scenarios in which the outcome of interest occurs at or more frequently than one event/100 person-years. We illustrate a process to assess whether sequential statistical analyses of registry data performed via distributed networks may prove a worthwhile infrastructure investment for pharmacovigilance.
Park, Ji Eun; Han, Kyunghwa; Sung, Yu Sub; Chung, Mi Sun; Koo, Hyun Jung; Yoon, Hee Mang; Choi, Young Jun; Lee, Seung Soo; Kim, Kyung Won; Shin, Youngbin; An, Suah; Cho, Hyo-Min
2017-01-01
Objective To evaluate the frequency and adequacy of statistical analyses in a general radiology journal when reporting a reliability analysis for a diagnostic test. Materials and Methods Sixty-three studies of diagnostic test accuracy (DTA) and 36 studies reporting reliability analyses published in the Korean Journal of Radiology between 2012 and 2016 were analyzed. Studies were judged using the methodological guidelines of the Radiological Society of North America-Quantitative Imaging Biomarkers Alliance (RSNA-QIBA), and COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) initiative. DTA studies were evaluated by nine editorial board members of the journal. Reliability studies were evaluated by study reviewers experienced with reliability analysis. Results Thirty-one (49.2%) of the 63 DTA studies did not include a reliability analysis when deemed necessary. Among the 36 reliability studies, proper statistical methods were used in all (5/5) studies dealing with dichotomous/nominal data, 46.7% (7/15) of studies dealing with ordinal data, and 95.2% (20/21) of studies dealing with continuous data. Statistical methods were described in sufficient detail regarding weighted kappa in 28.6% (2/7) of studies and regarding the model and assumptions of intraclass correlation coefficient in 35.3% (6/17) and 29.4% (5/17) of studies, respectively. Reliability parameters were used as if they were agreement parameters in 23.1% (3/13) of studies. Reproducibility and repeatability were used incorrectly in 20% (3/15) of studies. Conclusion Greater attention to the importance of reporting reliability, thorough description of the related statistical methods, efforts not to neglect agreement parameters, and better use of relevant terminology is necessary. PMID:29089821
The Problem of Auto-Correlation in Parasitology
Pollitt, Laura C.; Reece, Sarah E.; Mideo, Nicole; Nussey, Daniel H.; Colegrave, Nick
2012-01-01
Explaining the contribution of host and pathogen factors in driving infection dynamics is a major ambition in parasitology. There is increasing recognition that analyses based on single summary measures of an infection (e.g., peak parasitaemia) do not adequately capture infection dynamics and so, the appropriate use of statistical techniques to analyse dynamics is necessary to understand infections and, ultimately, control parasites. However, the complexities of within-host environments mean that tracking and analysing pathogen dynamics within infections and among hosts poses considerable statistical challenges. Simple statistical models make assumptions that will rarely be satisfied in data collected on host and parasite parameters. In particular, model residuals (unexplained variance in the data) should not be correlated in time or space. Here we demonstrate how failure to account for such correlations can result in incorrect biological inference from statistical analysis. We then show how mixed effects models can be used as a powerful tool to analyse such repeated measures data in the hope that this will encourage better statistical practices in parasitology. PMID:22511865
Is everything we eat associated with cancer? A systematic cookbook review.
Schoenfeld, Jonathan D; Ioannidis, John P A
2013-01-01
Nutritional epidemiology is a highly prolific field. Debates on associations of nutrients with disease risk are common in the literature and attract attention in public media. We aimed to examine the conclusions, statistical significance, and reproducibility in the literature on associations between specific foods and cancer risk. We selected 50 common ingredients from random recipes in a cookbook. PubMed queries identified recent studies that evaluated the relation of each ingredient to cancer risk. Information regarding author conclusions and relevant effect estimates were extracted. When >10 articles were found, we focused on the 10 most recent articles. Forty ingredients (80%) had articles reporting on their cancer risk. Of 264 single-study assessments, 191 (72%) concluded that the tested food was associated with an increased (n = 103) or a decreased (n = 88) risk; 75% of the risk estimates had weak (0.05 > P ≥ 0.001) or no statistical (P > 0.05) significance. Statistically significant results were more likely than nonsignificant findings to be published in the study abstract than in only the full text (P < 0.0001). Meta-analyses (n = 36) presented more conservative results; only 13 (26%) reported an increased (n = 4) or a decreased (n = 9) risk (6 had more than weak statistical support). The median RRs (IQRs) for studies that concluded an increased or a decreased risk were 2.20 (1.60, 3.44) and 0.52 (0.39, 0.66), respectively. The RRs from the meta-analyses were on average null (median: 0.96; IQR: 0.85, 1.10). Associations with cancer risk or benefits have been claimed for most food ingredients. Many single studies highlight implausibly large effects, even though evidence is weak. Effect sizes shrink in meta-analyses.
Interpretation of correlations in clinical research.
Hung, Man; Bounsanga, Jerry; Voss, Maren Wright
2017-11-01
Critically analyzing research is a key skill in evidence-based practice and requires knowledge of research methods, results interpretation, and applications, all of which rely on a foundation based in statistics. Evidence-based practice makes high demands on trained medical professionals to interpret an ever-expanding array of research evidence. As clinical training emphasizes medical care rather than statistics, it is useful to review the basics of statistical methods and what they mean for interpreting clinical studies. We reviewed the basic concepts of correlational associations, violations of normality, unobserved variable bias, sample size, and alpha inflation. The foundations of causal inference were discussed and sound statistical analyses were examined. We discuss four ways in which correlational analysis is misused, including causal inference overreach, over-reliance on significance, alpha inflation, and sample size bias. Recent published studies in the medical field provide evidence of causal assertion overreach drawn from correlational findings. The findings present a primer on the assumptions and nature of correlational methods of analysis and urge clinicians to exercise appropriate caution as they critically analyze the evidence before them and evaluate evidence that supports practice. Critically analyzing new evidence requires statistical knowledge in addition to clinical knowledge. Studies can overstate relationships, expressing causal assertions when only correlational evidence is available. Failure to account for the effect of sample size in the analyses tends to overstate the importance of predictive variables. It is important not to overemphasize the statistical significance without consideration of effect size and whether differences could be considered clinically meaningful.
Niclasen, Janni; Keilow, Maria; Obel, Carsten
2018-05-01
Well-being is considered a prerequisite for learning. The Danish Ministry of Education initiated the development of a new 40-item student well-being questionnaire in 2014 to monitor well-being among all Danish public school students on a yearly basis. The aim of this study was to investigate the basic psychometric properties of this questionnaire. We used the data from the 2015 Danish student well-being survey for 268,357 students in grades 4-9 (about 85% of the study population). Descriptive statistics, exploratory factor analyses, confirmatory factor analyses and Cronbach's α reliability measures were used in the analyses. The factor analyses did not unambiguously support one particular factor structure. However, based on the basic descriptive statistics, exploratory factor analyses, confirmatory factor analyses, the semantics of the individual items and Cronbach's α, we propose a four-factor structure including 27 of the 40 items originally proposed. The four scales measure school connectedness, learning self-efficacy, learning environment and classroom management. Two bullying items and two psychosomatic items should be considered separately, leaving 31 items in the questionnaire. The proposed four-factor structure addresses central aspects of well-being, which, if used constructively, may support public schools' work to increase levels of student well-being.
Mycology of chronic suppurative otitis media-cholesteatoma disease: An evaluative study.
Singh, Gautam Bir; Solo, Medozhanuo; Kaur, Ravinder; Arora, Rubeena; Kumar, Sunil
To detect the prevalence of fungus in chronic suppurative otitis media-cholesteatoma disease and to evaluate its clinical significance. Prospective observational study conducted in a sample size of 46 patients at a tertiary care university teaching hospital. Forty six patients suffering from chronic suppurative otitis media-cholesteatoma disease were recruited in this prospective study. Data was duly recorded. Cholesteatoma sample was procured at the time of mastoid surgery and microbiologically analysed for fungal infestation. Clinical correlation to fungus infestation of cholesteatoma was statistically analysed. Out of the recruited 46 patients, post-operatively cholesteatoma was seen in 40 cases only. Seventeen i.e. 42.5% of these cases had fungal colonization of cholesteatoma. Further a statistically significant correlation between persistent otorrhoea and fungal infestation of cholesteatoma was observed. Three cases of fungal otomastoiditis were also recorded in this study, but a statistically significant correlation between complications and fungus infestation of cholesteatoma could not be clearly established. There is fungal colonization of cholesteatoma which is pathogenic and can cause persistent otorrhoea. Copyright © 2017 Elsevier Inc. All rights reserved.
Chevance, Aurélie; Schuster, Tibor; Steele, Russell; Ternès, Nils; Platt, Robert W
2015-10-01
Robustness of an existing meta-analysis can justify decisions on whether to conduct an additional study addressing the same research question. We illustrate the graphical assessment of the potential impact of an additional study on an existing meta-analysis using published data on statin use and the risk of acute kidney injury. A previously proposed graphical augmentation approach is used to assess the sensitivity of the current test and heterogeneity statistics extracted from existing meta-analysis data. In addition, we extended the graphical augmentation approach to assess potential changes in the pooled effect estimate after updating a current meta-analysis and applied the three graphical contour definitions to data from meta-analyses on statin use and acute kidney injury risk. In the considered example data, the pooled effect estimates and heterogeneity indices demonstrated to be considerably robust to the addition of a future study. Supportingly, for some previously inconclusive meta-analyses, a study update might yield statistically significant kidney injury risk increase associated with higher statin exposure. The illustrated contour approach should become a standard tool for the assessment of the robustness of meta-analyses. It can guide decisions on whether to conduct additional studies addressing a relevant research question. Copyright © 2015 Elsevier Inc. All rights reserved.
Applying Beliefs and Resources Frameworks to the Psychometric Analyses of an Epistemology Survey
ERIC Educational Resources Information Center
Yerdelen-Damar, Sevda; Elby, Andrew; Eryilmaz, Ali
2012-01-01
This study explored how researchers' views about the form of students' epistemologies influence how the researchers develop and refine surveys and how they interpret survey results. After running standard statistical analyses on 505 physics students' responses to the Turkish version of the Maryland Physics Expectations-II survey, probing students'…
ERIC Educational Resources Information Center
Maric, Marija; Wiers, Reinout W.; Prins, Pier J. M.
2012-01-01
Despite guidelines and repeated calls from the literature, statistical mediation analysis in youth treatment outcome research is rare. Even more concerning is that many studies that "have" reported mediation analyses do not fulfill basic requirements for mediation analysis, providing inconclusive data and clinical implications. As a result, after…
Hemphill, Sheryl A; Heerde, Jessica A; Herrenkohl, Todd I; Farrington, David P
2016-01-01
In an influential 2002 paper, Farrington and colleagues argued that to understand ‘causes’ of delinquency, within-individual analyses of longitudinal data are required (compared to the vast majority of analyses that have focused on between-individual differences). The current paper aimed to complete similar analyses to those conducted by Farrington and colleagues by focusing on the developmental correlates and risk factors for antisocial behaviour and by comparing within-individual and between-individual predictors of antisocial behaviour using data from the youngest Victorian cohort of the International Youth Development Study, a state-wide representative sample of 927 students from Victoria, Australia. Data analysed in the current paper are from participants in Year 6 (age 11–12 years) in 2003 to Year 11 (age 16–17 years) in 2008 (N = 791; 85% retention) with data collected almost annually. Participants completed a self-report survey of risk and protective factors and antisocial behaviour. Complete data were available for 563 participants. The results of this study showed all but one of the forward- (family conflict) and backward-lagged (low attachment to parents) correlations were statistically significant for the within-individual analyses compared with all analyses being statistically significant for the between-individual analyses. In general, between-individual correlations were greater in magnitude than within-individual correlations. Given that forward-lagged within-individual correlations provide more salient measures of causes of delinquency, it is important that longitudinal studies with multi-wave data analyse and report their data using both between-individual and within-individual correlations to inform current prevention and early intervention programs seeking to reduce rates of antisocial behaviour. PMID:28123186
Zhang, Ying; Sun, Jin; Zhang, Yun-Jiao; Chai, Qian-Yun; Zhang, Kang; Ma, Hong-Li; Wu, Xiao-Ke; Liu, Jian-Ping
2016-10-21
Although Traditional Chinese Medicine (TCM) has been widely used in clinical settings, a major challenge that remains in TCM is to evaluate its efficacy scientifically. This randomized controlled trial aims to evaluate the efficacy and safety of berberine in the treatment of patients with polycystic ovary syndrome. In order to improve the transparency and research quality of this clinical trial, we prepared this statistical analysis plan (SAP). The trial design, primary and secondary outcomes, and safety outcomes were declared to reduce selection biases in data analysis and result reporting. We specified detailed methods for data management and statistical analyses. Statistics in corresponding tables, listings, and graphs were outlined. The SAP provided more detailed information than trial protocol on data management and statistical analysis methods. Any post hoc analyses could be identified via referring to this SAP, and the possible selection bias and performance bias will be reduced in the trial. This study is registered at ClinicalTrials.gov, NCT01138930 , registered on 7 June 2010.
1992-10-01
N=8) and Results of 44 Statistical Analyses for Impact Test Performed on Forefoot of Unworn Footwear A-2. Summary Statistics (N=8) and Results of...on Forefoot of Worn Footwear Vlll Tables (continued) Table Page B-2. Summary Statistics (N=4) and Results of 76 Statistical Analyses for Impact...used tests to assess heel and forefoot shock absorption, upper and sole durability, and flexibility (Cavanagh, 1978). Later, the number of tests was
2011-01-01
Background Clinical researchers have often preferred to use a fixed effects model for the primary interpretation of a meta-analysis. Heterogeneity is usually assessed via the well known Q and I2 statistics, along with the random effects estimate they imply. In recent years, alternative methods for quantifying heterogeneity have been proposed, that are based on a 'generalised' Q statistic. Methods We review 18 IPD meta-analyses of RCTs into treatments for cancer, in order to quantify the amount of heterogeneity present and also to discuss practical methods for explaining heterogeneity. Results Differing results were obtained when the standard Q and I2 statistics were used to test for the presence of heterogeneity. The two meta-analyses with the largest amount of heterogeneity were investigated further, and on inspection the straightforward application of a random effects model was not deemed appropriate. Compared to the standard Q statistic, the generalised Q statistic provided a more accurate platform for estimating the amount of heterogeneity in the 18 meta-analyses. Conclusions Explaining heterogeneity via the pre-specification of trial subgroups, graphical diagnostic tools and sensitivity analyses produced a more desirable outcome than an automatic application of the random effects model. Generalised Q statistic methods for quantifying and adjusting for heterogeneity should be incorporated as standard into statistical software. Software is provided to help achieve this aim. PMID:21473747
Vesterinen, Hanna M; Vesterinen, Hanna V; Egan, Kieren; Deister, Amelie; Schlattmann, Peter; Macleod, Malcolm R; Dirnagl, Ulrich
2011-04-01
Translating experimental findings into clinically effective therapies is one of the major bottlenecks of modern medicine. As this has been particularly true for cerebrovascular research, attention has turned to the quality and validity of experimental cerebrovascular studies. We set out to assess the study design, statistical analyses, and reporting of cerebrovascular research. We assessed all original articles published in the Journal of Cerebral Blood Flow and Metabolism during the year 2008 against a checklist designed to capture the key attributes relating to study design, statistical analyses, and reporting. A total of 156 original publications were included (animal, in vitro, human). Few studies reported a primary research hypothesis, statement of purpose, or measures to safeguard internal validity (such as randomization, blinding, exclusion or inclusion criteria). Many studies lacked sufficient information regarding methods and results to form a reasonable judgment about their validity. In nearly 20% of studies, statistical tests were either not appropriate or information to allow assessment of appropriateness was lacking. This study identifies a number of factors that should be addressed if the quality of research in basic and translational biomedicine is to be improved. We support the widespread implementation of the ARRIVE (Animal Research Reporting In Vivo Experiments) statement for the reporting of experimental studies in biomedicine, for improving training in proper study design and analysis, and that reviewers and editors adopt a more constructively critical approach in the assessment of manuscripts for publication.
Vesterinen, Hanna V; Egan, Kieren; Deister, Amelie; Schlattmann, Peter; Macleod, Malcolm R; Dirnagl, Ulrich
2011-01-01
Translating experimental findings into clinically effective therapies is one of the major bottlenecks of modern medicine. As this has been particularly true for cerebrovascular research, attention has turned to the quality and validity of experimental cerebrovascular studies. We set out to assess the study design, statistical analyses, and reporting of cerebrovascular research. We assessed all original articles published in the Journal of Cerebral Blood Flow and Metabolism during the year 2008 against a checklist designed to capture the key attributes relating to study design, statistical analyses, and reporting. A total of 156 original publications were included (animal, in vitro, human). Few studies reported a primary research hypothesis, statement of purpose, or measures to safeguard internal validity (such as randomization, blinding, exclusion or inclusion criteria). Many studies lacked sufficient information regarding methods and results to form a reasonable judgment about their validity. In nearly 20% of studies, statistical tests were either not appropriate or information to allow assessment of appropriateness was lacking. This study identifies a number of factors that should be addressed if the quality of research in basic and translational biomedicine is to be improved. We support the widespread implementation of the ARRIVE (Animal Research Reporting In Vivo Experiments) statement for the reporting of experimental studies in biomedicine, for improving training in proper study design and analysis, and that reviewers and editors adopt a more constructively critical approach in the assessment of manuscripts for publication. PMID:21157472
Ceppi, Marcello; Gallo, Fabio; Bonassi, Stefano
2011-01-01
The most common study design performed in population studies based on the micronucleus (MN) assay, is the cross-sectional study, which is largely performed to evaluate the DNA damaging effects of exposure to genotoxic agents in the workplace, in the environment, as well as from diet or lifestyle factors. Sample size is still a critical issue in the design of MN studies since most recent studies considering gene-environment interaction, often require a sample size of several hundred subjects, which is in many cases difficult to achieve. The control of confounding is another major threat to the validity of causal inference. The most popular confounders considered in population studies using MN are age, gender and smoking habit. Extensive attention is given to the assessment of effect modification, given the increasing inclusion of biomarkers of genetic susceptibility in the study design. Selected issues concerning the statistical treatment of data have been addressed in this mini-review, starting from data description, which is a critical step of statistical analysis, since it allows to detect possible errors in the dataset to be analysed and to check the validity of assumptions required for more complex analyses. Basic issues dealing with statistical analysis of biomarkers are extensively evaluated, including methods to explore the dose-response relationship among two continuous variables and inferential analysis. A critical approach to the use of parametric and non-parametric methods is presented, before addressing the issue of most suitable multivariate models to fit MN data. In the last decade, the quality of statistical analysis of MN data has certainly evolved, although even nowadays only a small number of studies apply the Poisson model, which is the most suitable method for the analysis of MN data.
Stopka, Thomas J; Goulart, Michael A; Meyers, David J; Hutcheson, Marga; Barton, Kerri; Onofrey, Shauna; Church, Daniel; Donahue, Ashley; Chui, Kenneth K H
2017-04-20
Hepatitis C virus (HCV) infections have increased during the past decade but little is known about geographic clustering patterns. We used a unique analytical approach, combining geographic information systems (GIS), spatial epidemiology, and statistical modeling to identify and characterize HCV hotspots, statistically significant clusters of census tracts with elevated HCV counts and rates. We compiled sociodemographic and HCV surveillance data (n = 99,780 cases) for Massachusetts census tracts (n = 1464) from 2002 to 2013. We used a five-step spatial epidemiological approach, calculating incremental spatial autocorrelations and Getis-Ord Gi* statistics to identify clusters. We conducted logistic regression analyses to determine factors associated with the HCV hotspots. We identified nine HCV clusters, with the largest in Boston, New Bedford/Fall River, Worcester, and Springfield (p < 0.05). In multivariable analyses, we found that HCV hotspots were independently and positively associated with the percent of the population that was Hispanic (adjusted odds ratio [AOR]: 1.07; 95% confidence interval [CI]: 1.04, 1.09) and the percent of households receiving food stamps (AOR: 1.83; 95% CI: 1.22, 2.74). HCV hotspots were independently and negatively associated with the percent of the population that were high school graduates or higher (AOR: 0.91; 95% CI: 0.89, 0.93) and the percent of the population in the "other" race/ethnicity category (AOR: 0.88; 95% CI: 0.85, 0.91). We identified locations where HCV clusters were a concern, and where enhanced HCV prevention, treatment, and care can help combat the HCV epidemic in Massachusetts. GIS, spatial epidemiological and statistical analyses provided a rigorous approach to identify hotspot clusters of disease, which can inform public health policy and intervention targeting. Further studies that incorporate spatiotemporal cluster analyses, Bayesian spatial and geostatistical models, spatially weighted regression analyses, and assessment of associations between HCV clustering and the built environment are needed to expand upon our combined spatial epidemiological and statistical methods.
Sullivan, Thomas R; Yelland, Lisa N; Lee, Katherine J; Ryan, Philip; Salter, Amy B
2017-08-01
After completion of a randomised controlled trial, an extended follow-up period may be initiated to learn about longer term impacts of the intervention. Since extended follow-up studies often involve additional eligibility restrictions and consent processes for participation, and a longer duration of follow-up entails a greater risk of participant attrition, missing data can be a considerable threat in this setting. As a potential source of bias, it is critical that missing data are appropriately handled in the statistical analysis, yet little is known about the treatment of missing data in extended follow-up studies. The aims of this review were to summarise the extent of missing data in extended follow-up studies and the use of statistical approaches to address this potentially serious problem. We performed a systematic literature search in PubMed to identify extended follow-up studies published from January to June 2015. Studies were eligible for inclusion if the original randomised controlled trial results were also published and if the main objective of extended follow-up was to compare the original randomised groups. We recorded information on the extent of missing data and the approach used to treat missing data in the statistical analysis of the primary outcome of the extended follow-up study. Of the 81 studies included in the review, 36 (44%) reported additional eligibility restrictions and 24 (30%) consent processes for entry into extended follow-up. Data were collected at a median of 7 years after randomisation. Excluding 28 studies with a time to event primary outcome, 51/53 studies (96%) reported missing data on the primary outcome. The median percentage of randomised participants with complete data on the primary outcome was just 66% in these studies. The most common statistical approach to address missing data was complete case analysis (51% of studies), while likelihood-based analyses were also well represented (25%). Sensitivity analyses around the missing data mechanism were rarely performed (25% of studies), and when they were, they often involved unrealistic assumptions about the mechanism. Despite missing data being a serious problem in extended follow-up studies, statistical approaches to addressing missing data were often inadequate. We recommend researchers clearly specify all sources of missing data in follow-up studies and use statistical methods that are valid under a plausible assumption about the missing data mechanism. Sensitivity analyses should also be undertaken to assess the robustness of findings to assumptions about the missing data mechanism.
Dissecting the genetics of complex traits using summary association statistics
Pasaniuc, Bogdan; Price, Alkes L.
2017-01-01
During the past decade, genome-wide association studies (GWAS) have successfully identified tens of thousands of genetic variants associated with complex traits and diseases. These studies have produced extensive repositories of genetic variation and trait measurements across large numbers of individuals, providing tremendous opportunities for further analyses. However, privacy concerns and other logistical considerations often limit access to individual-level genetic data, motivating the development of methods that analyze summary association statistics. Here we review recent progress on statistical methods that leverage summary association data to gain insights into the genetic basis of complex traits and diseases. PMID:27840428
Methodological and Reporting Quality of Systematic Reviews and Meta-analyses in Endodontics.
Nagendrababu, Venkateshbabu; Pulikkotil, Shaju Jacob; Sultan, Omer Sheriff; Jayaraman, Jayakumar; Peters, Ove A
2018-06-01
The aim of this systematic review (SR) was to evaluate the quality of SRs and meta-analyses (MAs) in endodontics. A comprehensive literature search was conducted to identify relevant articles in the electronic databases from January 2000 to June 2017. Two reviewers independently assessed the articles for eligibility and data extraction. SRs and MAs on interventional studies with a minimum of 2 therapeutic strategies in endodontics were included in this SR. Methodologic and reporting quality were assessed using A Measurement Tool to Assess Systematic Reviews (AMSTAR) and Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA), respectively. The interobserver reliability was calculated using the Cohen kappa statistic. Statistical analysis with the level of significance at P < .05 was performed using Kruskal-Wallis tests and simple linear regression analysis. A total of 30 articles were selected for the current SR. Using AMSTAR, the item related to the scientific quality of studies used in conclusion was adhered by less than 40% of studies. Using PRISMA, 3 items were reported by less than 40% of studies, which were on objectives, protocol registration, and funding. No association was evident comparing the number of authors and country with quality. Statistical significance was observed when quality was compared among journals, with studies published as Cochrane reviews superior to those published in other journals. AMSTAR and PRISMA scores were significantly related. SRs in endodontics showed variability in both methodologic and reporting quality. Copyright © 2018 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.
OdorMapComparer: an application for quantitative analyses and comparisons of fMRI brain odor maps.
Liu, Nian; Xu, Fuqiang; Miller, Perry L; Shepherd, Gordon M
2007-01-01
Brain odor maps are reconstructed flat images that describe the spatial activity patterns in the glomerular layer of the olfactory bulbs in animals exposed to different odor stimuli. We have developed a software application, OdorMapComparer, to carry out quantitative analyses and comparisons of the fMRI odor maps. This application is an open-source window program that first loads two odor map images being compared. It allows image transformations including scaling, flipping, rotating, and warping so that the two images can be appropriately aligned to each other. It performs simple subtraction, addition, and average of signals in the two images. It also provides comparative statistics including the normalized correlation (NC) and spatial correlation coefficient. Experimental studies showed that the rodent fMRI odor maps for aliphatic aldehydes displayed spatial activity patterns that are similar in gross outlines but somewhat different in specific subregions. Analyses with OdorMapComparer indicate that the similarity between odor maps decreases with increasing difference in the length of carbon chains. For example, the map of butanal is more closely related to that of pentanal (with a NC = 0.617) than to that of octanal (NC = 0.082), which is consistent with animal behavioral studies. The study also indicates that fMRI odor maps are statistically odor-specific and repeatable across both the intra- and intersubject trials. OdorMapComparer thus provides a tool for quantitative, statistical analyses and comparisons of fMRI odor maps in a fashion that is integrated with the overall odor mapping techniques.
Valdez-Flores, Ciriaco; Sielken, Robert L; Teta, M Jane
2010-04-01
The most recent epidemiological data on individual workers in the NIOSH and updated UCC occupational studies have been used to characterize the potential excess cancer risks of environmental exposure to ethylene oxide (EO). In addition to refined analyses of the separate cohorts, power has been increased by analyzing the combined cohorts. In previous SMR analyses of the separate studies and the present analyses of the updated and pooled studies of over 19,000 workers, none of the SMRs for any combination of the 12 cancer endpoints and six sub-cohorts analyzed were statistically significantly greater than one including the ones of greatest previous interest: leukemia, lymphohematopoietic tissue, lymphoid tumors, NHL, and breast cancer. In our study, no evidence of a positive cumulative exposure-response relationship was found. Fitted Cox proportional hazards models with cumulative EO exposure do not have statistically significant positive slopes. The lack of increasing trends was corroborated by categorical analyses. Cox model estimates of the concentrations corresponding to a 1-in-a-million extra environmental cancer risk are all greater than approximately 1ppb and are more than 1500-fold greater than the 0.4ppt estimate in the 2006 EPA draft IRIS risk assessment. The reasons for this difference are identified and discussed. Copyright 2009 Elsevier Inc. All rights reserved.
van der Krieke, Lian; Emerencia, Ando C; Bos, Elisabeth H; Rosmalen, Judith Gm; Riese, Harriëtte; Aiello, Marco; Sytema, Sjoerd; de Jonge, Peter
2015-08-07
Health promotion can be tailored by combining ecological momentary assessments (EMA) with time series analysis. This combined method allows for studying the temporal order of dynamic relationships among variables, which may provide concrete indications for intervention. However, application of this method in health care practice is hampered because analyses are conducted manually and advanced statistical expertise is required. This study aims to show how this limitation can be overcome by introducing automated vector autoregressive modeling (VAR) of EMA data and to evaluate its feasibility through comparisons with results of previously published manual analyses. We developed a Web-based open source application, called AutoVAR, which automates time series analyses of EMA data and provides output that is intended to be interpretable by nonexperts. The statistical technique we used was VAR. AutoVAR tests and evaluates all possible VAR models within a given combinatorial search space and summarizes their results, thereby replacing the researcher's tasks of conducting the analysis, making an informed selection of models, and choosing the best model. We compared the output of AutoVAR to the output of a previously published manual analysis (n=4). An illustrative example consisting of 4 analyses was provided. Compared to the manual output, the AutoVAR output presents similar model characteristics and statistical results in terms of the Akaike information criterion, the Bayesian information criterion, and the test statistic of the Granger causality test. Results suggest that automated analysis and interpretation of times series is feasible. Compared to a manual procedure, the automated procedure is more robust and can save days of time. These findings may pave the way for using time series analysis for health promotion on a larger scale. AutoVAR was evaluated using the results of a previously conducted manual analysis. Analysis of additional datasets is needed in order to validate and refine the application for general use.
Jahn, I; Foraita, R
2008-01-01
In Germany gender-sensitive approaches are part of guidelines for good epidemiological practice as well as health reporting. They are increasingly claimed to realize the gender mainstreaming strategy in research funding by the federation and federal states. This paper focuses on methodological aspects of data analysis, as an empirical data example of which serves the health report of Bremen, a population-based cross-sectional study. Health reporting requires analysis and reporting methods that are able to discover sex/gender issues of questions, on the one hand, and consider how results can adequately be communicated, on the other hand. The core question is: Which consequences do a different inclusion of the category sex in different statistical analyses for identification of potential target groups have on the results? As evaluation methods logistic regressions as well as a two-stage procedure were exploratively conducted. This procedure combines graphical models with CHAID decision trees and allows for visualising complex results. Both methods are analysed by stratification as well as adjusted by sex/gender and compared with each other. As a result, only stratified analyses are able to detect differences between the sexes and within the sex/gender groups as long as one cannot resort to previous knowledge. Adjusted analyses can detect sex/gender differences only if interaction terms have been included in the model. Results are discussed from a statistical-epidemiological perspective as well as in the context of health reporting. As a conclusion, the question, if a statistical method is gender-sensitive, can only be answered by having concrete research questions and known conditions. Often, an appropriate statistic procedure can be chosen after conducting a separate analysis for women and men. Future gender studies deserve innovative study designs as well as conceptual distinctiveness with regard to the biological and the sociocultural elements of the category sex/gender.
Emerencia, Ando C; Bos, Elisabeth H; Rosmalen, Judith GM; Riese, Harriëtte; Aiello, Marco; Sytema, Sjoerd; de Jonge, Peter
2015-01-01
Background Health promotion can be tailored by combining ecological momentary assessments (EMA) with time series analysis. This combined method allows for studying the temporal order of dynamic relationships among variables, which may provide concrete indications for intervention. However, application of this method in health care practice is hampered because analyses are conducted manually and advanced statistical expertise is required. Objective This study aims to show how this limitation can be overcome by introducing automated vector autoregressive modeling (VAR) of EMA data and to evaluate its feasibility through comparisons with results of previously published manual analyses. Methods We developed a Web-based open source application, called AutoVAR, which automates time series analyses of EMA data and provides output that is intended to be interpretable by nonexperts. The statistical technique we used was VAR. AutoVAR tests and evaluates all possible VAR models within a given combinatorial search space and summarizes their results, thereby replacing the researcher’s tasks of conducting the analysis, making an informed selection of models, and choosing the best model. We compared the output of AutoVAR to the output of a previously published manual analysis (n=4). Results An illustrative example consisting of 4 analyses was provided. Compared to the manual output, the AutoVAR output presents similar model characteristics and statistical results in terms of the Akaike information criterion, the Bayesian information criterion, and the test statistic of the Granger causality test. Conclusions Results suggest that automated analysis and interpretation of times series is feasible. Compared to a manual procedure, the automated procedure is more robust and can save days of time. These findings may pave the way for using time series analysis for health promotion on a larger scale. AutoVAR was evaluated using the results of a previously conducted manual analysis. Analysis of additional datasets is needed in order to validate and refine the application for general use. PMID:26254160
The Deployment Life Study: Longitudinal Analysis of Military Families Across the Deployment Cycle
2016-01-01
psychological and physical aggression than they reported prior to the deployment. 1 H. Fischer, A Guide to U.S. Military Casualty Statistics ...analyses include a large number of statistical tests and thus the results pre- sented in this report should be viewed in terms of patterns, rather...Military Children and Families,” The Future of Children, Vol. 23, No. 2, 2013, pp. 13–39. Fischer, H., A Guide to U.S. Military Casualty Statistics
40 CFR 91.512 - Request for public hearing.
Code of Federal Regulations, 2010 CFR
2010-07-01
... plans and statistical analyses have been properly applied (specifically, whether sampling procedures and statistical analyses specified in this subpart were followed and whether there exists a basis for... will be made available to the public during Agency business hours. ...
Neyeloff, Jeruza L; Fuchs, Sandra C; Moreira, Leila B
2012-01-20
Meta-analyses are necessary to synthesize data obtained from primary research, and in many situations reviews of observational studies are the only available alternative. General purpose statistical packages can meta-analyze data, but usually require external macros or coding. Commercial specialist software is available, but may be expensive and focused in a particular type of primary data. Most available softwares have limitations in dealing with descriptive data, and the graphical display of summary statistics such as incidence and prevalence is unsatisfactory. Analyses can be conducted using Microsoft Excel, but there was no previous guide available. We constructed a step-by-step guide to perform a meta-analysis in a Microsoft Excel spreadsheet, using either fixed-effect or random-effects models. We have also developed a second spreadsheet capable of producing customized forest plots. It is possible to conduct a meta-analysis using only Microsoft Excel. More important, to our knowledge this is the first description of a method for producing a statistically adequate but graphically appealing forest plot summarizing descriptive data, using widely available software.
2012-01-01
Background Meta-analyses are necessary to synthesize data obtained from primary research, and in many situations reviews of observational studies are the only available alternative. General purpose statistical packages can meta-analyze data, but usually require external macros or coding. Commercial specialist software is available, but may be expensive and focused in a particular type of primary data. Most available softwares have limitations in dealing with descriptive data, and the graphical display of summary statistics such as incidence and prevalence is unsatisfactory. Analyses can be conducted using Microsoft Excel, but there was no previous guide available. Findings We constructed a step-by-step guide to perform a meta-analysis in a Microsoft Excel spreadsheet, using either fixed-effect or random-effects models. We have also developed a second spreadsheet capable of producing customized forest plots. Conclusions It is possible to conduct a meta-analysis using only Microsoft Excel. More important, to our knowledge this is the first description of a method for producing a statistically adequate but graphically appealing forest plot summarizing descriptive data, using widely available software. PMID:22264277
ERIC Educational Resources Information Center
Cafri, Guy; Kromrey, Jeffrey D.; Brannick, Michael T.
2010-01-01
This article uses meta-analyses published in "Psychological Bulletin" from 1995 to 2005 to describe meta-analyses in psychology, including examination of statistical power, Type I errors resulting from multiple comparisons, and model choice. Retrospective power estimates indicated that univariate categorical and continuous moderators, individual…
Implementation of Head Start Planned Variation: 1970-1971. Part II.
ERIC Educational Resources Information Center
Lukas, Carol Van Deusen; Wohlleb, Cynthia
This volume of appendices is Part II of a study of program implementation in 12 models of Head Start Planned Variation. It presents details of the data analysis, copies of data collection instruments, and additional analyses and statistics. The appendices are: (A) Analysis of Variance Designs, (B) Copies of Instruments, (C) Additional Analyses,…
ERIC Educational Resources Information Center
Yeom, Min-ho
2016-01-01
The paper critically reviews the results of Korean massification in higher education (HE) and focuses on the consequences related to graduate employment. By analysing statistical data and reviewing related articles, this study explores the process of the massification of HE, investigates major factors influencing the expansion, and analyses and…
ERIC Educational Resources Information Center
James, William H.; Moore, David D.
1999-01-01
Examines the relationship between gender and drug use among adolescents using diagnostic assessments and biochemical analyses of urine samples. Statistical significance was found in the relationship between gender and marijuana use. The study confirms that more research is needed in this area. (Author/MKA)
Smith, Paul F.
2017-01-01
Effective inferential statistical analysis is essential for high quality studies in neuroscience. However, recently, neuroscience has been criticised for the poor use of experimental design and statistical analysis. Many of the statistical issues confronting neuroscience are similar to other areas of biology; however, there are some that occur more regularly in neuroscience studies. This review attempts to provide a succinct overview of some of the major issues that arise commonly in the analyses of neuroscience data. These include: the non-normal distribution of the data; inequality of variance between groups; extensive correlation in data for repeated measurements across time or space; excessive multiple testing; inadequate statistical power due to small sample sizes; pseudo-replication; and an over-emphasis on binary conclusions about statistical significance as opposed to effect sizes. Statistical analysis should be viewed as just another neuroscience tool, which is critical to the final outcome of the study. Therefore, it needs to be done well and it is a good idea to be proactive and seek help early, preferably before the study even begins. PMID:29371855
Smith, Paul F
2017-01-01
Effective inferential statistical analysis is essential for high quality studies in neuroscience. However, recently, neuroscience has been criticised for the poor use of experimental design and statistical analysis. Many of the statistical issues confronting neuroscience are similar to other areas of biology; however, there are some that occur more regularly in neuroscience studies. This review attempts to provide a succinct overview of some of the major issues that arise commonly in the analyses of neuroscience data. These include: the non-normal distribution of the data; inequality of variance between groups; extensive correlation in data for repeated measurements across time or space; excessive multiple testing; inadequate statistical power due to small sample sizes; pseudo-replication; and an over-emphasis on binary conclusions about statistical significance as opposed to effect sizes. Statistical analysis should be viewed as just another neuroscience tool, which is critical to the final outcome of the study. Therefore, it needs to be done well and it is a good idea to be proactive and seek help early, preferably before the study even begins.
Algorithm for Identifying Erroneous Rain-Gauge Readings
NASA Technical Reports Server (NTRS)
Rickman, Doug
2005-01-01
An algorithm analyzes rain-gauge data to identify statistical outliers that could be deemed to be erroneous readings. Heretofore, analyses of this type have been performed in burdensome manual procedures that have involved subjective judgements. Sometimes, the analyses have included computational assistance for detecting values falling outside of arbitrary limits. The analyses have been performed without statistically valid knowledge of the spatial and temporal variations of precipitation within rain events. In contrast, the present algorithm makes it possible to automate such an analysis, makes the analysis objective, takes account of the spatial distribution of rain gauges in conjunction with the statistical nature of spatial variations in rainfall readings, and minimizes the use of arbitrary criteria. The algorithm implements an iterative process that involves nonparametric statistics.
A weighted U-statistic for genetic association analyses of sequencing data.
Wei, Changshuai; Li, Ming; He, Zihuai; Vsevolozhskaya, Olga; Schaid, Daniel J; Lu, Qing
2014-12-01
With advancements in next-generation sequencing technology, a massive amount of sequencing data is generated, which offers a great opportunity to comprehensively investigate the role of rare variants in the genetic etiology of complex diseases. Nevertheless, the high-dimensional sequencing data poses a great challenge for statistical analysis. The association analyses based on traditional statistical methods suffer substantial power loss because of the low frequency of genetic variants and the extremely high dimensionality of the data. We developed a Weighted U Sequencing test, referred to as WU-SEQ, for the high-dimensional association analysis of sequencing data. Based on a nonparametric U-statistic, WU-SEQ makes no assumption of the underlying disease model and phenotype distribution, and can be applied to a variety of phenotypes. Through simulation studies and an empirical study, we showed that WU-SEQ outperformed a commonly used sequence kernel association test (SKAT) method when the underlying assumptions were violated (e.g., the phenotype followed a heavy-tailed distribution). Even when the assumptions were satisfied, WU-SEQ still attained comparable performance to SKAT. Finally, we applied WU-SEQ to sequencing data from the Dallas Heart Study (DHS), and detected an association between ANGPTL 4 and very low density lipoprotein cholesterol. © 2014 WILEY PERIODICALS, INC.
Regression methods for spatially correlated data: an example using beetle attacks in a seed orchard
Preisler Haiganoush; Nancy G. Rappaport; David L. Wood
1997-01-01
We present a statistical procedure for studying the simultaneous effects of observed covariates and unmeasured spatial variables on responses of interest. The procedure uses regression type analyses that can be used with existing statistical software packages. An example using the rate of twig beetle attacks on Douglas-fir trees in a seed orchard illustrates the...
Citation of previous meta-analyses on the same topic: a clue to perpetuation of incorrect methods?
Li, Tianjing; Dickersin, Kay
2013-06-01
Systematic reviews and meta-analyses serve as a basis for decision-making and clinical practice guidelines and should be carried out using appropriate methodology to avoid incorrect inferences. We describe the characteristics, statistical methods used for meta-analyses, and citation patterns of all 21 glaucoma systematic reviews we identified pertaining to the effectiveness of prostaglandin analog eye drops in treating primary open-angle glaucoma, published between December 2000 and February 2012. We abstracted data, assessed whether appropriate statistical methods were applied in meta-analyses, and examined citation patterns of included reviews. We identified two forms of problematic statistical analyses in 9 of the 21 systematic reviews examined. Except in 1 case, none of the 9 reviews that used incorrect statistical methods cited a previously published review that used appropriate methods. Reviews that used incorrect methods were cited 2.6 times more often than reviews that used appropriate statistical methods. We speculate that by emulating the statistical methodology of previous systematic reviews, systematic review authors may have perpetuated incorrect approaches to meta-analysis. The use of incorrect statistical methods, perhaps through emulating methods described in previous research, calls conclusions of systematic reviews into question and may lead to inappropriate patient care. We urge systematic review authors and journal editors to seek the advice of experienced statisticians before undertaking or accepting for publication a systematic review and meta-analysis. The author(s) have no proprietary or commercial interest in any materials discussed in this article. Copyright © 2013 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.
Comparative effectiveness research methodology using secondary data: A starting user's guide.
Sun, Maxine; Lipsitz, Stuart R
2018-04-01
The use of secondary data, such as claims or administrative data, in comparative effectiveness research has grown tremendously in recent years. We believe that the current review can help investigators relying on secondary data to (1) gain insight into both the methodologies and statistical methods, (2) better understand the necessity of a rigorous planning before initiating a comparative effectiveness investigation, and (3) optimize the quality of their investigations. Specifically, we review concepts of adjusted analyses and confounders, methods of propensity score analyses, and instrumental variable analyses, risk prediction models (logistic and time-to-event), decision-curve analysis, as well as the interpretation of the P value and hypothesis testing. Overall, we hope that the current review article can help research investigators relying on secondary data to perform comparative effectiveness research better understand the necessity of a rigorous planning before study start, and gain better insight in the choice of statistical methods so as to optimize the quality of the research study. Copyright © 2017 Elsevier Inc. All rights reserved.
A Framework for Assessing High School Students' Statistical Reasoning.
Chan, Shiau Wei; Ismail, Zaleha; Sumintono, Bambang
2016-01-01
Based on a synthesis of literature, earlier studies, analyses and observations on high school students, this study developed an initial framework for assessing students' statistical reasoning about descriptive statistics. Framework descriptors were established across five levels of statistical reasoning and four key constructs. The former consisted of idiosyncratic reasoning, verbal reasoning, transitional reasoning, procedural reasoning, and integrated process reasoning. The latter include describing data, organizing and reducing data, representing data, and analyzing and interpreting data. In contrast to earlier studies, this initial framework formulated a complete and coherent statistical reasoning framework. A statistical reasoning assessment tool was then constructed from this initial framework. The tool was administered to 10 tenth-grade students in a task-based interview. The initial framework was refined, and the statistical reasoning assessment tool was revised. The ten students then participated in the second task-based interview, and the data obtained were used to validate the framework. The findings showed that the students' statistical reasoning levels were consistent across the four constructs, and this result confirmed the framework's cohesion. Developed to contribute to statistics education, this newly developed statistical reasoning framework provides a guide for planning learning goals and designing instruction and assessments.
A Framework for Assessing High School Students' Statistical Reasoning
2016-01-01
Based on a synthesis of literature, earlier studies, analyses and observations on high school students, this study developed an initial framework for assessing students’ statistical reasoning about descriptive statistics. Framework descriptors were established across five levels of statistical reasoning and four key constructs. The former consisted of idiosyncratic reasoning, verbal reasoning, transitional reasoning, procedural reasoning, and integrated process reasoning. The latter include describing data, organizing and reducing data, representing data, and analyzing and interpreting data. In contrast to earlier studies, this initial framework formulated a complete and coherent statistical reasoning framework. A statistical reasoning assessment tool was then constructed from this initial framework. The tool was administered to 10 tenth-grade students in a task-based interview. The initial framework was refined, and the statistical reasoning assessment tool was revised. The ten students then participated in the second task-based interview, and the data obtained were used to validate the framework. The findings showed that the students’ statistical reasoning levels were consistent across the four constructs, and this result confirmed the framework’s cohesion. Developed to contribute to statistics education, this newly developed statistical reasoning framework provides a guide for planning learning goals and designing instruction and assessments. PMID:27812091
Guerrero, Luis; Guàrdia, Maria Dolors; Xicola, Joan; Verbeke, Wim; Vanhonacker, Filiep; Zakowska-Biemans, Sylwia; Sajdakowska, Marta; Sulmont-Rossé, Claire; Issanchou, Sylvie; Contel, Michele; Scalvedi, M Luisa; Granli, Britt Signe; Hersleth, Margrethe
2009-04-01
Traditional food products (TFP) are an important part of European culture, identity, and heritage. In order to maintain and expand the market share of TFP, further improvement in safety, health, or convenience is needed by means of different innovations. The aim of this study was to obtain a consumer-driven definition for the concept of TFP and innovation and to compare these across six European countries (Belgium, France, Italy, Norway, Poland and Spain) by means of semantic and textual statistical analyses. Twelve focus groups were performed, two per country, under similar conditions. The transcriptions obtained were submitted to an ordinary semantic analysis and to a textual statistical analysis using the software ALCESTE. Four main dimensions were identified for the concept of TFP: habit-natural, origin-locality, processing-elaboration and sensory properties. Five dimensions emerged around the concept of innovation: novelty-change, variety, processing-technology, origin-ethnicity and convenience. TFP were similarly perceived in the countries analysed, while some differences were detected for the concept of innovation. Semantic and statistical analyses of the focus groups led to similar results for both concepts. In some cases and according to the consumers' point of view the application of innovations may damage the traditional character of TFP.
Ramón, M; Martínez-Pastor, F
2018-04-23
Computer-aided sperm analysis (CASA) produces a wealth of data that is frequently ignored. The use of multiparametric statistical methods can help explore these datasets, unveiling the subpopulation structure of sperm samples. In this review we analyse the significance of the internal heterogeneity of sperm samples and its relevance. We also provide a brief description of the statistical tools used for extracting sperm subpopulations from the datasets, namely unsupervised clustering (with non-hierarchical, hierarchical and two-step methods) and the most advanced supervised methods, based on machine learning. The former method has allowed exploration of subpopulation patterns in many species, whereas the latter offering further possibilities, especially considering functional studies and the practical use of subpopulation analysis. We also consider novel approaches, such as the use of geometric morphometrics or imaging flow cytometry. Finally, although the data provided by CASA systems provides valuable information on sperm samples by applying clustering analyses, there are several caveats. Protocols for capturing and analysing motility or morphometry should be standardised and adapted to each experiment, and the algorithms should be open in order to allow comparison of results between laboratories. Moreover, we must be aware of new technology that could change the paradigm for studying sperm motility and morphology.
Chen, C; Xiang, J Y; Hu, W; Xie, Y B; Wang, T J; Cui, J W; Xu, Y; Liu, Z; Xiang, H; Xie, Q
2015-11-01
To screen and identify safe micro-organisms used during Douchi fermentation, and verify the feasibility of producing high-quality Douchi using these identified micro-organisms. PCR-denaturing gradient gel electrophoresis (DGGE) and automatic amino-acid analyser were used to investigate the microbial diversity and free amino acids (FAAs) content of 10 commercial Douchi samples. The correlations between microbial communities and FAAs were analysed by statistical analysis. Ten strains with significant positive correlation were identified. Then an experiment on Douchi fermentation by identified strains was carried out, and the nutritional composition in Douchi was analysed. Results showed that FAAs and relative content of isoflavone aglycones in verification Douchi samples were generally higher than those in commercial Douchi samples. Our study indicated that fungi, yeasts, Bacillus and lactic acid bacteria were the key players in Douchi fermentation, and with identified probiotic micro-organisms participating in fermentation, a higher quality Douchi product was produced. This is the first report to analyse and confirm the key micro-organisms during Douchi fermentation by statistical analysis. This work proves fermentation micro-organisms to be the key influencing factor of Douchi quality, and demonstrates the feasibility of fermenting Douchi using identified starter micro-organisms. © 2015 The Society for Applied Microbiology.
Statistical analyses of commercial vehicle accident factors. Volume 1 Part 1
DOT National Transportation Integrated Search
1978-02-01
Procedures for conducting statistical analyses of commercial vehicle accidents have been established and initially applied. A file of some 3,000 California Highway Patrol accident reports from two areas of California during a period of about one year...
40 CFR 90.712 - Request for public hearing.
Code of Federal Regulations, 2010 CFR
2010-07-01
... sampling plans and statistical analyses have been properly applied (specifically, whether sampling procedures and statistical analyses specified in this subpart were followed and whether there exists a basis... Clerk and will be made available to the public during Agency business hours. ...
2013-01-01
Introduction Small-study effects refer to the fact that trials with limited sample sizes are more likely to report larger beneficial effects than large trials. However, this has never been investigated in critical care medicine. Thus, the present study aimed to examine the presence and extent of small-study effects in critical care medicine. Methods Critical care meta-analyses involving randomized controlled trials and reported mortality as an outcome measure were considered eligible for the study. Component trials were classified as large (≥100 patients per arm) and small (<100 patients per arm) according to their sample sizes. Ratio of odds ratio (ROR) was calculated for each meta-analysis and then RORs were combined using a meta-analytic approach. ROR<1 indicated larger beneficial effect in small trials. Small and large trials were compared in methodological qualities including sequence generating, blinding, allocation concealment, intention to treat and sample size calculation. Results A total of 27 critical care meta-analyses involving 317 trials were included. Of them, five meta-analyses showed statistically significant RORs <1, and other meta-analyses did not reach a statistical significance. Overall, the pooled ROR was 0.60 (95% CI: 0.53 to 0.68); the heterogeneity was moderate with an I2 of 50.3% (chi-squared = 52.30; P = 0.002). Large trials showed significantly better reporting quality than small trials in terms of sequence generating, allocation concealment, blinding, intention to treat, sample size calculation and incomplete follow-up data. Conclusions Small trials are more likely to report larger beneficial effects than large trials in critical care medicine, which could be partly explained by the lower methodological quality in small trials. Caution should be practiced in the interpretation of meta-analyses involving small trials. PMID:23302257
Page, Matthew J; McKenzie, Joanne E; Kirkham, Jamie; Dwan, Kerry; Kramer, Sharon; Green, Sally; Forbes, Andrew
2014-10-01
Systematic reviews may be compromised by selective inclusion and reporting of outcomes and analyses. Selective inclusion occurs when there are multiple effect estimates in a trial report that could be included in a particular meta-analysis (e.g. from multiple measurement scales and time points) and the choice of effect estimate to include in the meta-analysis is based on the results (e.g. statistical significance, magnitude or direction of effect). Selective reporting occurs when the reporting of a subset of outcomes and analyses in the systematic review is based on the results (e.g. a protocol-defined outcome is omitted from the published systematic review). To summarise the characteristics and synthesise the results of empirical studies that have investigated the prevalence of selective inclusion or reporting in systematic reviews of randomised controlled trials (RCTs), investigated the factors (e.g. statistical significance or direction of effect) associated with the prevalence and quantified the bias. We searched the Cochrane Methodology Register (to July 2012), Ovid MEDLINE, Ovid EMBASE, Ovid PsycINFO and ISI Web of Science (each up to May 2013), and the US Agency for Healthcare Research and Quality (AHRQ) Effective Healthcare Program's Scientific Resource Center (SRC) Methods Library (to June 2013). We also searched the abstract books of the 2011 and 2012 Cochrane Colloquia and the article alerts for methodological work in research synthesis published from 2009 to 2011 and compiled in Research Synthesis Methods. We included both published and unpublished empirical studies that investigated the prevalence and factors associated with selective inclusion or reporting, or both, in systematic reviews of RCTs of healthcare interventions. We included empirical studies assessing any type of selective inclusion or reporting, such as investigations of how frequently RCT outcome data is selectively included in systematic reviews based on the results, outcomes and analyses are discrepant between protocol and published review or non-significant outcomes are partially reported in the full text or summary within systematic reviews. Two review authors independently selected empirical studies for inclusion, extracted the data and performed a risk of bias assessment. A third review author resolved any disagreements about inclusion or exclusion of empirical studies, data extraction and risk of bias. We contacted authors of included studies for additional unpublished data. Primary outcomes included overall prevalence of selective inclusion or reporting, association between selective inclusion or reporting and the statistical significance of the effect estimate, and association between selective inclusion or reporting and the direction of the effect estimate. We combined prevalence estimates and risk ratios (RRs) using a random-effects meta-analysis model. Seven studies met the inclusion criteria. No studies had investigated selective inclusion of results in systematic reviews, or discrepancies in outcomes and analyses between systematic review registry entries and published systematic reviews. Based on a meta-analysis of four studies (including 485 Cochrane Reviews), 38% (95% confidence interval (CI) 23% to 54%) of systematic reviews added, omitted, upgraded or downgraded at least one outcome between the protocol and published systematic review. The association between statistical significance and discrepant outcome reporting between protocol and published systematic review was uncertain. The meta-analytic estimate suggested an increased risk of adding or upgrading (i.e. changing a secondary outcome to primary) when the outcome was statistically significant, although the 95% CI included no association and a decreased risk as plausible estimates (RR 1.43, 95% CI 0.71 to 2.85; two studies, n = 552 meta-analyses). Also, the meta-analytic estimate suggested an increased risk of downgrading (i.e. changing a primary outcome to secondary) when the outcome was statistically significant, although the 95% CI included no association and a decreased risk as plausible estimates (RR 1.26, 95% CI 0.60 to 2.62; two studies, n = 484 meta-analyses). None of the included studies had investigated whether the association between statistical significance and adding, upgrading or downgrading of outcomes was modified by the type of comparison, direction of effect or type of outcome; or whether there is an association between direction of the effect estimate and discrepant outcome reporting.Several secondary outcomes were reported in the included studies. Two studies found that reasons for discrepant outcome reporting were infrequently reported in published systematic reviews (6% in one study and 22% in the other). One study (including 62 Cochrane Reviews) found that 32% (95% CI 21% to 45%) of systematic reviews did not report all primary outcomes in the abstract. Another study (including 64 Cochrane and 118 non-Cochrane reviews) found that statistically significant primary outcomes were more likely to be completely reported in the systematic review abstract than non-significant primary outcomes (RR 2.66, 95% CI 1.81 to 3.90). None of the studies included systematic reviews published after 2009 when reporting standards for systematic reviews (Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) Statement, and Methodological Expectations of Cochrane Intervention Reviews (MECIR)) were disseminated, so the results might not be generalisable to more recent systematic reviews. Discrepant outcome reporting between the protocol and published systematic review is fairly common, although the association between statistical significance and discrepant outcome reporting is uncertain. Complete reporting of outcomes in systematic review abstracts is associated with statistical significance of the results for those outcomes. Systematic review outcomes and analysis plans should be specified prior to seeing the results of included studies to minimise post-hoc decisions that may be based on the observed results. Modifications that occur once the review has commenced, along with their justification, should be clearly reported. Effect estimates and CIs should be reported for all systematic review outcomes regardless of the results. The lack of research on selective inclusion of results in systematic reviews needs to be addressed and studies that avoid the methodological weaknesses of existing research are also needed.
Torres-Carvajal, Omar; Schulte, James A; Cadle, John E
2006-04-01
The South American iguanian lizard genus Stenocercus includes 54 species occurring mostly in the Andes and adjacent lowland areas from northern Venezuela and Colombia to central Argentina at elevations of 0-4000m. Small taxon or character sampling has characterized all phylogenetic analyses of Stenocercus, which has long been recognized as sister taxon to the Tropidurus Group. In this study, we use mtDNA sequence data to perform phylogenetic analyses that include 32 species of Stenocercus and 12 outgroup taxa. Monophyly of this genus is strongly supported by maximum parsimony and Bayesian analyses. Evolutionary relationships within Stenocercus are further analyzed with a Bayesian implementation of a general mixture model, which accommodates variability in the pattern of evolution across sites. These analyses indicate a basal split of Stenocercus into two clades, one of which receives very strong statistical support. In addition, we test previous hypotheses using non-parametric and parametric statistical methods, and provide a phylogenetic classification for Stenocercus.
Plant Taxonomy as a Field Study
ERIC Educational Resources Information Center
Dalby, D. H.
1970-01-01
Suggests methods of teaching plant identification and taxonomic theory using keys, statistical analyses, and biometrics. Population variation, genotype- environment interaction and experimental taxonomy are used in laboratory and field. (AL)
Angstman, Nicholas B; Frank, Hans-Georg; Schmitz, Christoph
2016-01-01
As a widely used and studied model organism, Caenorhabditis elegans worms offer the ability to investigate implications of behavioral change. Although, investigation of C. elegans behavioral traits has been shown, analysis is often narrowed down to measurements based off a single point, and thus cannot pick up on subtle behavioral and morphological changes. In the present study videos were captured of four different C. elegans strains grown in liquid cultures and transferred to NGM-agar plates with an E. coli lawn or with no lawn. Using an advanced software, WormLab, the full skeleton and outline of worms were tracked to determine whether the presence of food affects behavioral traits. In all seven investigated parameters, statistically significant differences were found in worm behavior between those moving on NGM-agar plates with an E. coli lawn and NGM-agar plates with no lawn. Furthermore, multiple test groups showed differences in interaction between variables as the parameters that significantly correlated statistically with speed of locomotion varied. In the present study, we demonstrate the validity of a model to analyze C. elegans behavior beyond simple speed of locomotion. The need to account for a nested design while performing statistical analyses in similar studies is also demonstrated. With extended analyses, C. elegans behavioral change can be investigated with greater sensitivity, which could have wide utility in fields such as, but not limited to, toxicology, drug discovery, and RNAi screening.
Supply Chain Collaboration: Information Sharing in a Tactical Operating Environment
2013-06-01
architecture, there are four tiers: Client (Web Application Clients ), Presentation (Web-Server), Processing (Application-Server), Data (Database...organization in each period. This data will be collected to analyze. i) Analyses and Validation: We will do a statistics test in this data, Pareto ...notes, outstanding deliveries, and inventory. i) Analyses and Validation: We will do a statistics test in this data, Pareto analyses and confirmation
Across-cohort QC analyses of GWAS summary statistics from complex traits.
Chen, Guo-Bo; Lee, Sang Hong; Robinson, Matthew R; Trzaskowski, Maciej; Zhu, Zhi-Xiang; Winkler, Thomas W; Day, Felix R; Croteau-Chonka, Damien C; Wood, Andrew R; Locke, Adam E; Kutalik, Zoltán; Loos, Ruth J F; Frayling, Timothy M; Hirschhorn, Joel N; Yang, Jian; Wray, Naomi R; Visscher, Peter M
2016-01-01
Genome-wide association studies (GWASs) have been successful in discovering SNP trait associations for many quantitative traits and common diseases. Typically, the effect sizes of SNP alleles are very small and this requires large genome-wide association meta-analyses (GWAMAs) to maximize statistical power. A trend towards ever-larger GWAMA is likely to continue, yet dealing with summary statistics from hundreds of cohorts increases logistical and quality control problems, including unknown sample overlap, and these can lead to both false positive and false negative findings. In this study, we propose four metrics and visualization tools for GWAMA, using summary statistics from cohort-level GWASs. We propose methods to examine the concordance between demographic information, and summary statistics and methods to investigate sample overlap. (I) We use the population genetics F st statistic to verify the genetic origin of each cohort and their geographic location, and demonstrate using GWAMA data from the GIANT Consortium that geographic locations of cohorts can be recovered and outlier cohorts can be detected. (II) We conduct principal component analysis based on reported allele frequencies, and are able to recover the ancestral information for each cohort. (III) We propose a new statistic that uses the reported allelic effect sizes and their standard errors to identify significant sample overlap or heterogeneity between pairs of cohorts. (IV) To quantify unknown sample overlap across all pairs of cohorts, we propose a method that uses randomly generated genetic predictors that does not require the sharing of individual-level genotype data and does not breach individual privacy.
Across-cohort QC analyses of GWAS summary statistics from complex traits
Chen, Guo-Bo; Lee, Sang Hong; Robinson, Matthew R; Trzaskowski, Maciej; Zhu, Zhi-Xiang; Winkler, Thomas W; Day, Felix R; Croteau-Chonka, Damien C; Wood, Andrew R; Locke, Adam E; Kutalik, Zoltán; Loos, Ruth J F; Frayling, Timothy M; Hirschhorn, Joel N; Yang, Jian; Wray, Naomi R; Visscher, Peter M
2017-01-01
Genome-wide association studies (GWASs) have been successful in discovering SNP trait associations for many quantitative traits and common diseases. Typically, the effect sizes of SNP alleles are very small and this requires large genome-wide association meta-analyses (GWAMAs) to maximize statistical power. A trend towards ever-larger GWAMA is likely to continue, yet dealing with summary statistics from hundreds of cohorts increases logistical and quality control problems, including unknown sample overlap, and these can lead to both false positive and false negative findings. In this study, we propose four metrics and visualization tools for GWAMA, using summary statistics from cohort-level GWASs. We propose methods to examine the concordance between demographic information, and summary statistics and methods to investigate sample overlap. (I) We use the population genetics Fst statistic to verify the genetic origin of each cohort and their geographic location, and demonstrate using GWAMA data from the GIANT Consortium that geographic locations of cohorts can be recovered and outlier cohorts can be detected. (II) We conduct principal component analysis based on reported allele frequencies, and are able to recover the ancestral information for each cohort. (III) We propose a new statistic that uses the reported allelic effect sizes and their standard errors to identify significant sample overlap or heterogeneity between pairs of cohorts. (IV) To quantify unknown sample overlap across all pairs of cohorts, we propose a method that uses randomly generated genetic predictors that does not require the sharing of individual-level genotype data and does not breach individual privacy. PMID:27552965
Webster, R J; Williams, A; Marchetti, F; Yauk, C L
2018-07-01
Mutations in germ cells pose potential genetic risks to offspring. However, de novo mutations are rare events that are spread across the genome and are difficult to detect. Thus, studies in this area have generally been under-powered, and no human germ cell mutagen has been identified. Whole Genome Sequencing (WGS) of human pedigrees has been proposed as an approach to overcome these technical and statistical challenges. WGS enables analysis of a much wider breadth of the genome than traditional approaches. Here, we performed power analyses to determine the feasibility of using WGS in human families to identify germ cell mutagens. Different statistical models were compared in the power analyses (ANOVA and multiple regression for one-child families, and mixed effect model sampling between two to four siblings per family). Assumptions were made based on parameters from the existing literature, such as the mutation-by-paternal age effect. We explored two scenarios: a constant effect due to an exposure that occurred in the past, and an accumulating effect where the exposure is continuing. Our analysis revealed the importance of modeling inter-family variability of the mutation-by-paternal age effect. Statistical power was improved by models accounting for the family-to-family variability. Our power analyses suggest that sufficient statistical power can be attained with 4-28 four-sibling families per treatment group, when the increase in mutations ranges from 40 to 10% respectively. Modeling family variability using mixed effect models provided a reduction in sample size compared to a multiple regression approach. Much larger sample sizes were required to detect an interaction effect between environmental exposures and paternal age. These findings inform study design and statistical modeling approaches to improve power and reduce sequencing costs for future studies in this area. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.
Research of Extension of the Life Cycle of Helicopter Rotor Blade in Hungary
2003-02-01
Radiography (DXR), and (iii) Vibration Diagnostics (VD) with Statistical Energy Analysis (SEA) were semi- simultaneously applied [1]. The used three...2.2. Vibration Diagnostics (VD)) Parallel to the NDT measurements the Statistical Energy Analysis (SEA) as a vibration diagnostical tool were...noises were analysed with a dual-channel real time frequency analyser (BK2035). In addition to the Statistical Energy Analysis measurement a small
Sunspot activity and influenza pandemics: a statistical assessment of the purported association.
Towers, S
2017-10-01
Since 1978, a series of papers in the literature have claimed to find a significant association between sunspot activity and the timing of influenza pandemics. This paper examines these analyses, and attempts to recreate the three most recent statistical analyses by Ertel (1994), Tapping et al. (2001), and Yeung (2006), which all have purported to find a significant relationship between sunspot numbers and pandemic influenza. As will be discussed, each analysis had errors in the data. In addition, in each analysis arbitrary selections or assumptions were also made, and the authors did not assess the robustness of their analyses to changes in those arbitrary assumptions. Varying the arbitrary assumptions to other, equally valid, assumptions negates the claims of significance. Indeed, an arbitrary selection made in one of the analyses appears to have resulted in almost maximal apparent significance; changing it only slightly yields a null result. This analysis applies statistically rigorous methodology to examine the purported sunspot/pandemic link, using more statistically powerful un-binned analysis methods, rather than relying on arbitrarily binned data. The analyses are repeated using both the Wolf and Group sunspot numbers. In all cases, no statistically significant evidence of any association was found. However, while the focus in this particular analysis was on the purported relationship of influenza pandemics to sunspot activity, the faults found in the past analyses are common pitfalls; inattention to analysis reproducibility and robustness assessment are common problems in the sciences, that are unfortunately not noted often enough in review.
Gaskin, Cadeyrn J; Happell, Brenda
2013-02-01
Having sufficient power to detect effect sizes of an expected magnitude is a core consideration when designing studies in which inferential statistics will be used. The main aim of this study was to investigate the statistical power in studies published in the International Journal of Mental Health Nursing. From volumes 19 (2010) and 20 (2011) of the journal, studies were analysed for their power to detect small, medium, and large effect sizes, according to Cohen's guidelines. The power of the 23 studies included in this review to detect small, medium, and large effects was 0.34, 0.79, and 0.94, respectively. In 90% of papers, no adjustments for experiment-wise error were reported. With a median of nine inferential tests per paper, the mean experiment-wise error rate was 0.51. A priori power analyses were only reported in 17% of studies. Although effect sizes for correlations and regressions were routinely reported, effect sizes for other tests (χ(2)-tests, t-tests, ANOVA/MANOVA) were largely absent from the papers. All types of effect sizes were infrequently interpreted. Researchers are strongly encouraged to conduct power analyses when designing studies, and to avoid scattergun approaches to data analysis (i.e. undertaking large numbers of tests in the hope of finding 'significant' results). Because reviewing effect sizes is essential for determining the clinical significance of study findings, researchers would better serve the field of mental health nursing if they reported and interpreted effect sizes. © 2012 The Authors. International Journal of Mental Health Nursing © 2012 Australian College of Mental Health Nurses Inc.
NASA Technical Reports Server (NTRS)
Salstein, D. A.; Rosen, R. D.
1982-01-01
A study using the analyses produced from the assimilation cycle of parallel model runs that both include and withhold satellite data was undertaken. The analyzed state of the atmosphere is performed using data from a certain test period during the first Special Observing Period (SOP) of the Global Weather Experiment (FGGE).
How can my research paper be useful for future meta-analyses on forest restoration practices?
Enrique Andivia; Pedro Villar‑Salvador; Juan A. Oliet; Jaime Puertolas; R. Kasten Dumroese
2018-01-01
Statistical meta-analysis is a powerful and useful tool to quantitatively synthesize the information conveyed in published studies on a particular topic. It allows identifying and quantifying overall patterns and exploring causes of variation. The inclusion of published works in meta-analyses requires, however, a minimum quality standard of the reported data and...
The Influence of Experimental Design on the Detection of Performance Differences
ERIC Educational Resources Information Center
Bates, B. T.; Dufek, J. S.; James, C. R.; Harry, J. R.; Eggleston, J. D.
2016-01-01
We demonstrate the effect of sample and trial size on statistical outcomes for single-subject analyses (SSA) and group analyses (GA) for a frequently studied performance activity and common intervention. Fifty strides of walking data collected in two blocks of 25 trials for two shoe conditions were analyzed for samples of five, eight, 10, and 12…
Machisa, Mercilene; Wichmann, Janine; Nyasulu, Peter S
2013-09-01
This study is the second to investigate the association between the use of biomass fuels (BMF) for household cooking and anaemia and stunting in children. Such fuels include coal, charcoal, wood, dung and crop residues. Data from the 2006-2007 Swaziland Demographic and Health Survey (a cross-sectional study design) were analysed. Childhood stunting was ascertained through age and height, and anaemia through haemoglobin measurement. The association between BMF use and health outcomes was determined in multinomial logistic regression analyses. Various confounders were considered in the analyses. A total of 1150 children aged 6-36 months were included in the statistical analyses, of these 596 (51.8%) and 317 (27.6%) were anaemic and stunted, respectively. BMF use was not significantly associated with childhood anaemia in univariate analysis. Independent risk factors for childhood anaemia were child's age, history of childhood diarrhoea and mother's anaemia status. No statistically significant association was observed between BMF use and childhood stunting, after adjusting for child's gender, age, birth weight and preceding birth interval. This study identified the need to prioritize childhood anaemia and stunting as health outcomes and the introduction of public health interventions in Swaziland. Further research is needed globally on the potential effects of BMF use on childhood anaemia and stunting.
Hu, Ting; Pan, Qinxin; Andrew, Angeline S; Langer, Jillian M; Cole, Michael D; Tomlinson, Craig R; Karagas, Margaret R; Moore, Jason H
2014-04-11
Several different genetic and environmental factors have been identified as independent risk factors for bladder cancer in population-based studies. Recent studies have turned to understanding the role of gene-gene and gene-environment interactions in determining risk. We previously developed the bioinformatics framework of statistical epistasis networks (SEN) to characterize the global structure of interacting genetic factors associated with a particular disease or clinical outcome. By applying SEN to a population-based study of bladder cancer among Caucasians in New Hampshire, we were able to identify a set of connected genetic factors with strong and significant interaction effects on bladder cancer susceptibility. To support our statistical findings using networks, in the present study, we performed pathway enrichment analyses on the set of genes identified using SEN, and found that they are associated with the carcinogen benzo[a]pyrene, a component of tobacco smoke. We further carried out an mRNA expression microarray experiment to validate statistical genetic interactions, and to determine if the set of genes identified in the SEN were differentially expressed in a normal bladder cell line and a bladder cancer cell line in the presence or absence of benzo[a]pyrene. Significant nonrandom sets of genes from the SEN were found to be differentially expressed in response to benzo[a]pyrene in both the normal bladder cells and the bladder cancer cells. In addition, the patterns of gene expression were significantly different between these two cell types. The enrichment analyses and the gene expression microarray results support the idea that SEN analysis of bladder in population-based studies is able to identify biologically meaningful statistical patterns. These results bring us a step closer to a systems genetic approach to understanding cancer susceptibility that integrates population and laboratory-based studies.
ERIC Educational Resources Information Center
Tay, Louis; Drasgow, Fritz
2012-01-01
Two Monte Carlo simulation studies investigated the effectiveness of the mean adjusted X[superscript 2]/df statistic proposed by Drasgow and colleagues and, because of problems with the method, a new approach for assessing the goodness of fit of an item response theory model was developed. It has been previously recommended that mean adjusted…
Replication Unreliability in Psychology: Elusive Phenomena or “Elusive” Statistical Power?
Tressoldi, Patrizio E.
2012-01-01
The focus of this paper is to analyze whether the unreliability of results related to certain controversial psychological phenomena may be a consequence of their low statistical power. Applying the Null Hypothesis Statistical Testing (NHST), still the widest used statistical approach, unreliability derives from the failure to refute the null hypothesis, in particular when exact or quasi-exact replications of experiments are carried out. Taking as example the results of meta-analyses related to four different controversial phenomena, subliminal semantic priming, incubation effect for problem solving, unconscious thought theory, and non-local perception, it was found that, except for semantic priming on categorization, the statistical power to detect the expected effect size (ES) of the typical study, is low or very low. The low power in most studies undermines the use of NHST to study phenomena with moderate or low ESs. We conclude by providing some suggestions on how to increase the statistical power or use different statistical approaches to help discriminate whether the results obtained may or may not be used to support or to refute the reality of a phenomenon with small ES. PMID:22783215
An audit of the statistics and the comparison with the parameter in the population
NASA Astrophysics Data System (ADS)
Bujang, Mohamad Adam; Sa'at, Nadiah; Joys, A. Reena; Ali, Mariana Mohamad
2015-10-01
The sufficient sample size that is needed to closely estimate the statistics for particular parameters are use to be an issue. Although sample size might had been calculated referring to objective of the study, however, it is difficult to confirm whether the statistics are closed with the parameter for a particular population. All these while, guideline that uses a p-value less than 0.05 is widely used as inferential evidence. Therefore, this study had audited results that were analyzed from various sub sample and statistical analyses and had compared the results with the parameters in three different populations. Eight types of statistical analysis and eight sub samples for each statistical analysis were analyzed. Results found that the statistics were consistent and were closed to the parameters when the sample study covered at least 15% to 35% of population. Larger sample size is needed to estimate parameter that involve with categorical variables compared with numerical variables. Sample sizes with 300 to 500 are sufficient to estimate the parameters for medium size of population.
The analysis of morphometric data on rocky mountain wolves and artic wolves using statistical method
NASA Astrophysics Data System (ADS)
Ammar Shafi, Muhammad; Saifullah Rusiman, Mohd; Hamzah, Nor Shamsidah Amir; Nor, Maria Elena; Ahmad, Noor’ani; Azia Hazida Mohamad Azmi, Nur; Latip, Muhammad Faez Ab; Hilmi Azman, Ahmad
2018-04-01
Morphometrics is a quantitative analysis depending on the shape and size of several specimens. Morphometric quantitative analyses are commonly used to analyse fossil record, shape and size of specimens and others. The aim of the study is to find the differences between rocky mountain wolves and arctic wolves based on gender. The sample utilised secondary data which included seven variables as independent variables and two dependent variables. Statistical modelling was used in the analysis such was the analysis of variance (ANOVA) and multivariate analysis of variance (MANOVA). The results showed there exist differentiating results between arctic wolves and rocky mountain wolves based on independent factors and gender.
Levis, Angelo G; Minicuci, Nadia; Ricci, Paolo; Gennaro, Valerio; Garbisa, Spiridione
2011-06-17
Whether or not there is a relationship between use of mobile phones (analogue and digital cellulars, and cordless) and head tumour risk (brain tumours, acoustic neuromas, and salivary gland tumours) is still a matter of debate; progress requires a critical analysis of the methodological elements necessary for an impartial evaluation of contradictory studies. A close examination of the protocols and results from all case-control and cohort studies, pooled- and meta-analyses on head tumour risk for mobile phone users was carried out, and for each study the elements necessary for evaluating its reliability were identified. In addition, new meta-analyses of the literature data were undertaken. These were limited to subjects with mobile phone latency time compatible with the progression of the examined tumours, and with analysis of the laterality of head tumour localisation corresponding to the habitual laterality of mobile phone use. Blind protocols, free from errors, bias, and financial conditioning factors, give positive results that reveal a cause-effect relationship between long-term mobile phone use or latency and statistically significant increase of ipsilateral head tumour risk, with biological plausibility. Non-blind protocols, which instead are affected by errors, bias, and financial conditioning factors, give negative results with systematic underestimate of such risk. However, also in these studies a statistically significant increase in risk of ipsilateral head tumours is quite common after more than 10 years of mobile phone use or latency. The meta-analyses, our included, examining only data on ipsilateral tumours in subjects using mobile phones since or for at least 10 years, show large and statistically significant increases in risk of ipsilateral brain gliomas and acoustic neuromas. Our analysis of the literature studies and of the results from meta-analyses of the significant data alone shows an almost doubling of the risk of head tumours induced by long-term mobile phone use or latency.
2011-01-01
Background Whether or not there is a relationship between use of mobile phones (analogue and digital cellulars, and cordless) and head tumour risk (brain tumours, acoustic neuromas, and salivary gland tumours) is still a matter of debate; progress requires a critical analysis of the methodological elements necessary for an impartial evaluation of contradictory studies. Methods A close examination of the protocols and results from all case-control and cohort studies, pooled- and meta-analyses on head tumour risk for mobile phone users was carried out, and for each study the elements necessary for evaluating its reliability were identified. In addition, new meta-analyses of the literature data were undertaken. These were limited to subjects with mobile phone latency time compatible with the progression of the examined tumours, and with analysis of the laterality of head tumour localisation corresponding to the habitual laterality of mobile phone use. Results Blind protocols, free from errors, bias, and financial conditioning factors, give positive results that reveal a cause-effect relationship between long-term mobile phone use or latency and statistically significant increase of ipsilateral head tumour risk, with biological plausibility. Non-blind protocols, which instead are affected by errors, bias, and financial conditioning factors, give negative results with systematic underestimate of such risk. However, also in these studies a statistically significant increase in risk of ipsilateral head tumours is quite common after more than 10 years of mobile phone use or latency. The meta-analyses, our included, examining only data on ipsilateral tumours in subjects using mobile phones since or for at least 10 years, show large and statistically significant increases in risk of ipsilateral brain gliomas and acoustic neuromas. Conclusions Our analysis of the literature studies and of the results from meta-analyses of the significant data alone shows an almost doubling of the risk of head tumours induced by long-term mobile phone use or latency. PMID:21679472
Weighted Statistical Binning: Enabling Statistically Consistent Genome-Scale Phylogenetic Analyses
Bayzid, Md Shamsuzzoha; Mirarab, Siavash; Boussau, Bastien; Warnow, Tandy
2015-01-01
Because biological processes can result in different loci having different evolutionary histories, species tree estimation requires multiple loci from across multiple genomes. While many processes can result in discord between gene trees and species trees, incomplete lineage sorting (ILS), modeled by the multi-species coalescent, is considered to be a dominant cause for gene tree heterogeneity. Coalescent-based methods have been developed to estimate species trees, many of which operate by combining estimated gene trees, and so are called "summary methods". Because summary methods are generally fast (and much faster than more complicated coalescent-based methods that co-estimate gene trees and species trees), they have become very popular techniques for estimating species trees from multiple loci. However, recent studies have established that summary methods can have reduced accuracy in the presence of gene tree estimation error, and also that many biological datasets have substantial gene tree estimation error, so that summary methods may not be highly accurate in biologically realistic conditions. Mirarab et al. (Science 2014) presented the "statistical binning" technique to improve gene tree estimation in multi-locus analyses, and showed that it improved the accuracy of MP-EST, one of the most popular coalescent-based summary methods. Statistical binning, which uses a simple heuristic to evaluate "combinability" and then uses the larger sets of genes to re-calculate gene trees, has good empirical performance, but using statistical binning within a phylogenomic pipeline does not have the desirable property of being statistically consistent. We show that weighting the re-calculated gene trees by the bin sizes makes statistical binning statistically consistent under the multispecies coalescent, and maintains the good empirical performance. Thus, "weighted statistical binning" enables highly accurate genome-scale species tree estimation, and is also statistically consistent under the multi-species coalescent model. New data used in this study are available at DOI: http://dx.doi.org/10.6084/m9.figshare.1411146, and the software is available at https://github.com/smirarab/binning. PMID:26086579
Customer perceived service quality, satisfaction and loyalty in Indian private healthcare.
Kondasani, Rama Koteswara Rao; Panda, Rajeev Kumar
2015-01-01
The purpose of this paper is to analyse how perceived service quality and customer satisfaction lead to loyalty towards healthcare service providers. In total, 475 hospital patients participated in a questionnaire survey in five Indian private hospitals. Descriptive statistics, factor analysis, regression and correlation statistics were employed to analyse customer perceived service quality and how it leads to loyalty towards service providers. Results indicate that the service seeker-service provider relationship, quality of facilities and the interaction with supporting staff have a positive effect on customer perception. Findings help healthcare managers to formulate effective strategies to ensure a better quality of services to the customers. This study helps healthcare managers to build customer loyalty towards healthcare services, thereby attracting and gaining more customers. This paper will help healthcare managers and service providers to analyse customer perceptions and their loyalty towards Indian private healthcare services.
Analysis and meta-analysis of single-case designs: an introduction.
Shadish, William R
2014-04-01
The last 10 years have seen great progress in the analysis and meta-analysis of single-case designs (SCDs). This special issue includes five articles that provide an overview of current work on that topic, including standardized mean difference statistics, multilevel models, Bayesian statistics, and generalized additive models. Each article analyzes a common example across articles and presents syntax or macros for how to do them. These articles are followed by commentaries from single-case design researchers and journal editors. This introduction briefly describes each article and then discusses several issues that must be addressed before we can know what analyses will eventually be best to use in SCD research. These issues include modeling trend, modeling error covariances, computing standardized effect size estimates, assessing statistical power, incorporating more accurate models of outcome distributions, exploring whether Bayesian statistics can improve estimation given the small samples common in SCDs, and the need for annotated syntax and graphical user interfaces that make complex statistics accessible to SCD researchers. The article then discusses reasons why SCD researchers are likely to incorporate statistical analyses into their research more often in the future, including changing expectations and contingencies regarding SCD research from outside SCD communities, changes and diversity within SCD communities, corrections of erroneous beliefs about the relationship between SCD research and statistics, and demonstrations of how statistics can help SCD researchers better meet their goals. Copyright © 2013 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.
Periodontal disease and carotid atherosclerosis: A meta-analysis of 17,330 participants.
Zeng, Xian-Tao; Leng, Wei-Dong; Lam, Yat-Yin; Yan, Bryan P; Wei, Xue-Mei; Weng, Hong; Kwong, Joey S W
2016-01-15
The association between periodontal disease and carotid atherosclerosis has been evaluated primarily in single-center studies, and whether periodontal disease is an independent risk factor of carotid atherosclerosis remains uncertain. This meta-analysis aimed to evaluate the association between periodontal disease and carotid atherosclerosis. We searched PubMed and Embase for relevant observational studies up to February 20, 2015. Two authors independently extracted data from included studies, and odds ratios (ORs) with 95% confidence intervals (CIs) were calculated for overall and subgroup meta-analyses. Statistical heterogeneity was assessed by the chi-squared test (P<0.1 for statistical significance) and quantified by the I(2) statistic. Data analysis was conducted using the Comprehensive Meta-Analysis (CMA) software. Fifteen observational studies involving 17,330 participants were included in the meta-analysis. The overall pooled result showed that periodontal disease was associated with carotid atherosclerosis (OR: 1.27, 95% CI: 1.14-1.41; P<0.001) but statistical heterogeneity was substantial (I(2)=78.90%). Subgroup analysis of adjusted smoking and diabetes mellitus showed borderline significance (OR: 1.08; 95% CI: 1.00-1.18; P=0.05). Sensitivity and cumulative analyses both indicated that our results were robust. Findings of our meta-analysis indicated that the presence of periodontal disease was associated with carotid atherosclerosis; however, further large-scale, well-conducted clinical studies are needed to explore the precise risk of developing carotid atherosclerosis in patients with periodontal disease. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
ERIC Educational Resources Information Center
Kohler, Helmut
The purpose of this study was to analyze the available statistics concerning teachers in schools of general education in the Federal Republic of Germany. An analysis of the demographic structure of the pool of full-time teachers showed that in 1971 30 percent of the teachers were under age 30, and 50 percent were under age 35. It was expected that…
Do regional methods really help reduce uncertainties in flood frequency analyses?
NASA Astrophysics Data System (ADS)
Cong Nguyen, Chi; Payrastre, Olivier; Gaume, Eric
2013-04-01
Flood frequency analyses are often based on continuous measured series at gauge sites. However, the length of the available data sets is usually too short to provide reliable estimates of extreme design floods. To reduce the estimation uncertainties, the analyzed data sets have to be extended either in time, making use of historical and paleoflood data, or in space, merging data sets considered as statistically homogeneous to build large regional data samples. Nevertheless, the advantage of the regional analyses, the important increase of the size of the studied data sets, may be counterbalanced by the possible heterogeneities of the merged sets. The application and comparison of four different flood frequency analysis methods to two regions affected by flash floods in the south of France (Ardèche and Var) illustrates how this balance between the number of records and possible heterogeneities plays in real-world applications. The four tested methods are: (1) a local statistical analysis based on the existing series of measured discharges, (2) a local analysis valuating the existing information on historical floods, (3) a standard regional flood frequency analysis based on existing measured series at gauged sites and (4) a modified regional analysis including estimated extreme peak discharges at ungauged sites. Monte Carlo simulations are conducted to simulate a large number of discharge series with characteristics similar to the observed ones (type of statistical distributions, number of sites and records) to evaluate to which extent the results obtained on these case studies can be generalized. These two case studies indicate that even small statistical heterogeneities, which are not detected by the standard homogeneity tests implemented in regional flood frequency studies, may drastically limit the usefulness of such approaches. On the other hand, these result show that the valuation of information on extreme events, either historical flood events at gauged sites or estimated extremes at ungauged sites in the considered region, is an efficient way to reduce uncertainties in flood frequency studies.
Global atmospheric circulation statistics, 1000-1 mb
NASA Technical Reports Server (NTRS)
Randel, William J.
1992-01-01
The atlas presents atmospheric general circulation statistics derived from twelve years (1979-90) of daily National Meteorological Center (NMC) operational geopotential height analyses; it is an update of a prior atlas using data over 1979-1986. These global analyses are available on pressure levels covering 1000-1 mb (approximately 0-50 km). The geopotential grids are a combined product of the Climate Analysis Center (which produces analyses over 70-1 mb) and operational NMC analyses (over 1000-100 mb). Balance horizontal winds and hydrostatic temperatures are derived from the geopotential fields.
Development of the Statistical Reasoning in Biology Concept Inventory (SRBCI)
Deane, Thomas; Nomme, Kathy; Jeffery, Erica; Pollock, Carol; Birol, Gülnur
2016-01-01
We followed established best practices in concept inventory design and developed a 12-item inventory to assess student ability in statistical reasoning in biology (Statistical Reasoning in Biology Concept Inventory [SRBCI]). It is important to assess student thinking in this conceptual area, because it is a fundamental requirement of being statistically literate and associated skills are needed in almost all walks of life. Despite this, previous work shows that non–expert-like thinking in statistical reasoning is common, even after instruction. As science educators, our goal should be to move students along a novice-to-expert spectrum, which could be achieved with growing experience in statistical reasoning. We used item response theory analyses (the one-parameter Rasch model and associated analyses) to assess responses gathered from biology students in two populations at a large research university in Canada in order to test SRBCI’s robustness and sensitivity in capturing useful data relating to the students’ conceptual ability in statistical reasoning. Our analyses indicated that SRBCI is a unidimensional construct, with items that vary widely in difficulty and provide useful information about such student ability. SRBCI should be useful as a diagnostic tool in a variety of biology settings and as a means of measuring the success of teaching interventions designed to improve statistical reasoning skills. PMID:26903497
Influence of study goals on study design and execution.
Kirklin, J W; Blackstone, E H; Naftel, D C; Turner, M E
1997-12-01
From the viewpoint of a clinician who makes recommendations to patients about choosing from the multiple possible management schemes, quantitative information derived from statistical analyses of observational studies is useful. Although random assignment of therapy is optimal, appropriately performed studies in which therapy has been nonrandomly "assigned" are considered acceptable, albeit occasionally with limitations in inferences. The analyses are considered most useful when they generate multivariable equations suitable for predicting time-related outcomes in individual patients. Graphic presentations improve communication with patients and facilitate truly informed consent.
Quantifying the impact of between-study heterogeneity in multivariate meta-analyses
Jackson, Dan; White, Ian R; Riley, Richard D
2012-01-01
Measures that quantify the impact of heterogeneity in univariate meta-analysis, including the very popular I2 statistic, are now well established. Multivariate meta-analysis, where studies provide multiple outcomes that are pooled in a single analysis, is also becoming more commonly used. The question of how to quantify heterogeneity in the multivariate setting is therefore raised. It is the univariate R2 statistic, the ratio of the variance of the estimated treatment effect under the random and fixed effects models, that generalises most naturally, so this statistic provides our basis. This statistic is then used to derive a multivariate analogue of I2, which we call . We also provide a multivariate H2 statistic, the ratio of a generalisation of Cochran's heterogeneity statistic and its associated degrees of freedom, with an accompanying generalisation of the usual I2 statistic, . Our proposed heterogeneity statistics can be used alongside all the usual estimates and inferential procedures used in multivariate meta-analysis. We apply our methods to some real datasets and show how our statistics are equally appropriate in the context of multivariate meta-regression, where study level covariate effects are included in the model. Our heterogeneity statistics may be used when applying any procedure for fitting the multivariate random effects model. Copyright © 2012 John Wiley & Sons, Ltd. PMID:22763950
A Nonparametric Geostatistical Method For Estimating Species Importance
Andrew J. Lister; Rachel Riemann; Michael Hoppus
2001-01-01
Parametric statistical methods are not always appropriate for conducting spatial analyses of forest inventory data. Parametric geostatistical methods such as variography and kriging are essentially averaging procedures, and thus can be affected by extreme values. Furthermore, non normal distributions violate the assumptions of analyses in which test statistics are...
ERIC Educational Resources Information Center
Ellis, Barbara G.; Dick, Steven J.
1996-01-01
Employs the statistics-documentation portion of a word-processing program's grammar-check feature together with qualitative analyses to determine that Henry Watterson, long-time editor of the "Louisville Courier-Journal," was probably the South's famed Civil War correspondent "Shadow." (TB)
The effect of noise-induced variance on parameter recovery from reaction times.
Vadillo, Miguel A; Garaizar, Pablo
2016-03-31
Technical noise can compromise the precision and accuracy of the reaction times collected in psychological experiments, especially in the case of Internet-based studies. Although this noise seems to have only a small impact on traditional statistical analyses, its effects on model fit to reaction-time distributions remains unexplored. Across four simulations we study the impact of technical noise on parameter recovery from data generated from an ex-Gaussian distribution and from a Ratcliff Diffusion Model. Our results suggest that the impact of noise-induced variance tends to be limited to specific parameters and conditions. Although we encourage researchers to adopt all measures to reduce the impact of noise on reaction-time experiments, we conclude that the typical amount of noise-induced variance found in these experiments does not pose substantial problems for statistical analyses based on model fitting.
Clinical trials, epidemiology, and public confidence.
Seigel, Daniel
2003-11-15
Critics in the media have become wary of exaggerated research claims from clinical trials and epidemiological studies. Closer to home, reviews of published studies find a high frequency of poor quality in research methods, including those used for statistical analysis. The statistical literature has long recognized that questionable research findings can occur when investigators fail to set aside their own outcome preferences as they analyse and interpret data. These preferences can be related to financial interests, a concern for patients, peer recognition, and commitment to a hypothesis. Several analyses of published papers provide evidence of an association between financial conflicts of interest and reported results. If we are to regain professional and lay confidence in research findings some changes are required. Clinical journals need to develop more competence in the review of analytic methods and provide space for thorough discussion of published papers whose results are challenged. Graduate schools need to prepare students for the conflicting interests that surround the practice of statistics. Above all, each of us must recognize our responsibility to use analytic procedures that illuminate the research issues rather than those serving special interests. Copyright 2003 John Wiley & Sons, Ltd.
Application of multivariate statistical techniques in microbial ecology.
Paliy, O; Shankar, V
2016-03-01
Recent advances in high-throughput methods of molecular analyses have led to an explosion of studies generating large-scale ecological data sets. In particular, noticeable effect has been attained in the field of microbial ecology, where new experimental approaches provided in-depth assessments of the composition, functions and dynamic changes of complex microbial communities. Because even a single high-throughput experiment produces large amount of data, powerful statistical techniques of multivariate analysis are well suited to analyse and interpret these data sets. Many different multivariate techniques are available, and often it is not clear which method should be applied to a particular data set. In this review, we describe and compare the most widely used multivariate statistical techniques including exploratory, interpretive and discriminatory procedures. We consider several important limitations and assumptions of these methods, and we present examples of how these approaches have been utilized in recent studies to provide insight into the ecology of the microbial world. Finally, we offer suggestions for the selection of appropriate methods based on the research question and data set structure. © 2016 John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
El Sharawy, Mohamed S.; Gaafar, Gamal R.
2016-12-01
Both reservoir engineers and petrophysicists have been concerned about dividing a reservoir into zones for engineering and petrophysics purposes. Through decades, several techniques and approaches were introduced. Out of them, statistical reservoir zonation, stratigraphic modified Lorenz (SML) plot and the principal component and clustering analyses techniques were chosen to apply on the Nubian sandstone reservoir of Palaeozoic - Lower Cretaceous age, Gulf of Suez, Egypt, by using five adjacent wells. The studied reservoir consists mainly of sandstone with some intercalation of shale layers with varying thickness from one well to another. The permeability ranged from less than 1 md to more than 1000 md. The statistical reservoir zonation technique, depending on core permeability, indicated that the cored interval of the studied reservoir can be divided into two zones. Using reservoir properties such as porosity, bulk density, acoustic impedance and interval transit time indicated also two zones with an obvious variation in separation depth and zones continuity. The stratigraphic modified Lorenz (SML) plot indicated the presence of more than 9 flow units in the cored interval as well as a high degree of microscopic heterogeneity. On the other hand, principal component and cluster analyses, depending on well logging data (gamma ray, sonic, density and neutron), indicated that the whole reservoir can be divided at least into four electrofacies having a noticeable variation in reservoir quality, as correlated with the measured permeability. Furthermore, continuity or discontinuity of the reservoir zones can be determined using this analysis.
Histometric analyses of cancellous and cortical interface in autogenous bone grafting
Netto, Henrique Duque; Olate, Sergio; Klüppel, Leandro; do Carmo, Antonio Marcio Resende; Vásquez, Bélgica; Albergaria-Barbosa, Jose
2013-01-01
Surgical procedures involving the rehabilitation of the maxillofacial region frequently require bone grafts; the aim of this research was to evaluate the interface between recipient and graft with cortical or cancellous contact. 6 adult beagle dogs with 15 kg weight were included in the study. Under general anesthesia, an 8 mm diameter block was obtained from parietal bone of each animal and was put on the frontal bone with a 12 mm 1.5 screws. Was used the lag screw technique from better contact between the recipient and graft. 3-week and 6-week euthanized period were chosen for histometric evaluation. Hematoxylin-eosin was used in a histologic routine technique and histomorphometry was realized with IMAGEJ software. T test was used for data analyses with p<0.05 for statistical significance. The result show some differences in descriptive histology but non statistical differences in the interface between cortical or cancellous bone at 3 or 6 week; as natural, after 6 week of surgery, bone integration was better and statistically superior to 3-week analyses. We conclude that integration of cortical or cancellous bone can be usefully without differences. PMID:23923071
Hydrometeorological and statistical analyses of heavy rainfall in Midwestern USA
NASA Astrophysics Data System (ADS)
Thorndahl, S.; Smith, J. A.; Krajewski, W. F.
2012-04-01
During the last two decades the mid-western states of the United States of America has been largely afflicted by heavy flood producing rainfall. Several of these storms seem to have similar hydrometeorological properties in terms of pattern, track, evolution, life cycle, clustering, etc. which raise the question if it is possible to derive general characteristics of the space-time structures of these heavy storms. This is important in order to understand hydrometeorological features, e.g. how storms evolve and with what frequency we can expect extreme storms to occur. In the literature, most studies of extreme rainfall are based on point measurements (rain gauges). However, with high resolution and quality radar observation periods exceeding more than two decades, it is possible to do long-term spatio-temporal statistical analyses of extremes. This makes it possible to link return periods to distributed rainfall estimates and to study precipitation structures which cause floods. However, doing these statistical frequency analyses of rainfall based on radar observations introduces some different challenges, converting radar reflectivity observations to "true" rainfall, which are not problematic doing traditional analyses on rain gauge data. It is for example difficult to distinguish reflectivity from high intensity rain from reflectivity from other hydrometeors such as hail, especially using single polarization radars which are used in this study. Furthermore, reflectivity from bright band (melting layer) should be discarded and anomalous propagation should be corrected in order to produce valid statistics of extreme radar rainfall. Other challenges include combining observations from several radars to one mosaic, bias correction against rain gauges, range correction, ZR-relationships, etc. The present study analyzes radar rainfall observations from 1996 to 2011 based the American NEXRAD network of radars over an area covering parts of Iowa, Wisconsin, Illinois, and Lake Michigan. The radar observations are processed using Hydro-NEXRAD algorithms in order to produce rainfall estimates with a spatial resolution of 1 km and a temporal resolution of 15 min. The rainfall estimates are bias-corrected on a daily basis using a network of rain gauges. Besides a thorough evaluation of the different challenges in investigating heavy rain as described above the study includes suggestions for frequency analysis methods as well as studies of hydrometeorological features of single events.
ERIC Educational Resources Information Center
Brandon, Paul R.; Harrison, George M.; Lawton, Brian E.
2013-01-01
When evaluators plan site-randomized experiments, they must conduct the appropriate statistical power analyses. These analyses are most likely to be valid when they are based on data from the jurisdictions in which the studies are to be conducted. In this method note, we provide software code, in the form of a SAS macro, for producing statistical…
Link, J; Pachaly, J
1975-08-01
In a retrospective 18-month study the infusion therapy applied in a great anesthesia institute is examined. The data of the course of anesthesia recorded on magnetic tape by routine are analysed for this purpose bya computer with the statistical program SPSS. It could be proved that the behaviour of the several anesthetists is very different. Various correlations are discussed.
Sul, Jae Hoon; Bilow, Michael; Yang, Wen-Yun; Kostem, Emrah; Furlotte, Nick; He, Dan; Eskin, Eleazar
2016-03-01
Although genome-wide association studies (GWASs) have discovered numerous novel genetic variants associated with many complex traits and diseases, those genetic variants typically explain only a small fraction of phenotypic variance. Factors that account for phenotypic variance include environmental factors and gene-by-environment interactions (GEIs). Recently, several studies have conducted genome-wide gene-by-environment association analyses and demonstrated important roles of GEIs in complex traits. One of the main challenges in these association studies is to control effects of population structure that may cause spurious associations. Many studies have analyzed how population structure influences statistics of genetic variants and developed several statistical approaches to correct for population structure. However, the impact of population structure on GEI statistics in GWASs has not been extensively studied and nor have there been methods designed to correct for population structure on GEI statistics. In this paper, we show both analytically and empirically that population structure may cause spurious GEIs and use both simulation and two GWAS datasets to support our finding. We propose a statistical approach based on mixed models to account for population structure on GEI statistics. We find that our approach effectively controls population structure on statistics for GEIs as well as for genetic variants.
1993-08-01
subtitled "Simulation Data," consists of detailed infonrnation on the design parmneter variations tested, subsequent statistical analyses conducted...used with confidence during the design process. The data quality can be examined in various forms such as statistical analyses of measure of merit data...merit, such as time to capture or nmaximurn pitch rate, can be calculated from the simulation time history data. Statistical techniques are then used
NASA Astrophysics Data System (ADS)
Lørup, Jens Kristian; Refsgaard, Jens Christian; Mazvimavi, Dominic
1998-03-01
The purpose of this study was to identify and assess long-term impacts of land use change on catchment runoff in semi-arid Zimbabwe, based on analyses of long hydrological time series (25-50 years) from six medium-sized (200-1000 km 2) non-experimental rural catchments. A methodology combining common statistical methods with hydrological modelling was adopted in order to distinguish between the effects of climate variability and the effects of land use change. The hydrological model (NAM) was in general able to simulate the observed hydrographs very well during the reference period, thus providing a means to account for the effects of climate variability and hence strengthening the power of the subsequent statistical tests. In the test period the validated model was used to provide the runoff record which would have occurred in the absence of land use change. The analyses indicated a decrease in the annual runoff for most of the six catchments, with the largest changes occurring for catchments located within communal land, where large increases in population and agricultural intensity have taken place. However, the decrease was only statistically significant at the 5% level for one of the catchments.
Critical analysis of adsorption data statistically
NASA Astrophysics Data System (ADS)
Kaushal, Achla; Singh, S. K.
2017-10-01
Experimental data can be presented, computed, and critically analysed in a different way using statistics. A variety of statistical tests are used to make decisions about the significance and validity of the experimental data. In the present study, adsorption was carried out to remove zinc ions from contaminated aqueous solution using mango leaf powder. The experimental data was analysed statistically by hypothesis testing applying t test, paired t test and Chi-square test to (a) test the optimum value of the process pH, (b) verify the success of experiment and (c) study the effect of adsorbent dose in zinc ion removal from aqueous solutions. Comparison of calculated and tabulated values of t and χ 2 showed the results in favour of the data collected from the experiment and this has been shown on probability charts. K value for Langmuir isotherm was 0.8582 and m value for Freundlich adsorption isotherm obtained was 0.725, both are <1, indicating favourable isotherms. Karl Pearson's correlation coefficient values for Langmuir and Freundlich adsorption isotherms were obtained as 0.99 and 0.95 respectively, which show higher degree of correlation between the variables. This validates the data obtained for adsorption of zinc ions from the contaminated aqueous solution with the help of mango leaf powder.
Physiological Response and Habituation of Endangered Species to Military Training Activities
2009-11-01
Wasser. 2008. Long-term impacts of poaching on relatedness, stress physiology, and reproductive output of adult female African elephants . Conservation...Statistical analyses................................................................................................................ 19 Study 6: Impact of...Study 6: Impact of radio transmitters on northern cardinal parental investment and productivity
A decade of individual participant data meta-analyses: A review of current practice.
Simmonds, Mark; Stewart, Gavin; Stewart, Lesley
2015-11-01
Individual participant data (IPD) systematic reviews and meta-analyses are often considered to be the gold standard for meta-analysis. In the ten years since the first review into the methodology and reporting practice of IPD reviews was published much has changed in the field. This paper investigates current reporting and statistical practice in IPD systematic reviews. A systematic review was performed to identify systematic reviews that collected and analysed IPD. Data were extracted from each included publication on a variety of issues related to the reporting of IPD review process, and the statistical methods used. There has been considerable growth in the use of "one-stage" methods to perform IPD meta-analyses. The majority of reviews consider at least one covariate other than the primary intervention, either using subgroup analysis or including covariates in one-stage regression models. Random-effects analyses, however, are not often used. Reporting of review methods was often limited, with few reviews presenting a risk-of-bias assessment. Details on issues specific to the use of IPD were little reported, including how IPD were obtained; how data was managed and checked for consistency and errors; and for how many studies and participants IPD were sought and obtained. While the last ten years have seen substantial changes in how IPD meta-analyses are performed there remains considerable scope for improving the quality of reporting for both the process of IPD systematic reviews, and the statistical methods employed in them. It is to be hoped that the publication of the PRISMA-IPD guidelines specific to IPD reviews will improve reporting in this area. Copyright © 2015 Elsevier Inc. All rights reserved.
How Big of a Problem is Analytic Error in Secondary Analyses of Survey Data?
West, Brady T; Sakshaug, Joseph W; Aurelien, Guy Alain S
2016-01-01
Secondary analyses of survey data collected from large probability samples of persons or establishments further scientific progress in many fields. The complex design features of these samples improve data collection efficiency, but also require analysts to account for these features when conducting analysis. Unfortunately, many secondary analysts from fields outside of statistics, biostatistics, and survey methodology do not have adequate training in this area, and as a result may apply incorrect statistical methods when analyzing these survey data sets. This in turn could lead to the publication of incorrect inferences based on the survey data that effectively negate the resources dedicated to these surveys. In this article, we build on the results of a preliminary meta-analysis of 100 peer-reviewed journal articles presenting analyses of data from a variety of national health surveys, which suggested that analytic errors may be extremely prevalent in these types of investigations. We first perform a meta-analysis of a stratified random sample of 145 additional research products analyzing survey data from the Scientists and Engineers Statistical Data System (SESTAT), which describes features of the U.S. Science and Engineering workforce, and examine trends in the prevalence of analytic error across the decades used to stratify the sample. We once again find that analytic errors appear to be quite prevalent in these studies. Next, we present several example analyses of real SESTAT data, and demonstrate that a failure to perform these analyses correctly can result in substantially biased estimates with standard errors that do not adequately reflect complex sample design features. Collectively, the results of this investigation suggest that reviewers of this type of research need to pay much closer attention to the analytic methods employed by researchers attempting to publish or present secondary analyses of survey data.
How Big of a Problem is Analytic Error in Secondary Analyses of Survey Data?
West, Brady T.; Sakshaug, Joseph W.; Aurelien, Guy Alain S.
2016-01-01
Secondary analyses of survey data collected from large probability samples of persons or establishments further scientific progress in many fields. The complex design features of these samples improve data collection efficiency, but also require analysts to account for these features when conducting analysis. Unfortunately, many secondary analysts from fields outside of statistics, biostatistics, and survey methodology do not have adequate training in this area, and as a result may apply incorrect statistical methods when analyzing these survey data sets. This in turn could lead to the publication of incorrect inferences based on the survey data that effectively negate the resources dedicated to these surveys. In this article, we build on the results of a preliminary meta-analysis of 100 peer-reviewed journal articles presenting analyses of data from a variety of national health surveys, which suggested that analytic errors may be extremely prevalent in these types of investigations. We first perform a meta-analysis of a stratified random sample of 145 additional research products analyzing survey data from the Scientists and Engineers Statistical Data System (SESTAT), which describes features of the U.S. Science and Engineering workforce, and examine trends in the prevalence of analytic error across the decades used to stratify the sample. We once again find that analytic errors appear to be quite prevalent in these studies. Next, we present several example analyses of real SESTAT data, and demonstrate that a failure to perform these analyses correctly can result in substantially biased estimates with standard errors that do not adequately reflect complex sample design features. Collectively, the results of this investigation suggest that reviewers of this type of research need to pay much closer attention to the analytic methods employed by researchers attempting to publish or present secondary analyses of survey data. PMID:27355817
Metaprop: a Stata command to perform meta-analysis of binomial data.
Nyaga, Victoria N; Arbyn, Marc; Aerts, Marc
2014-01-01
Meta-analyses have become an essential tool in synthesizing evidence on clinical and epidemiological questions derived from a multitude of similar studies assessing the particular issue. Appropriate and accessible statistical software is needed to produce the summary statistic of interest. Metaprop is a statistical program implemented to perform meta-analyses of proportions in Stata. It builds further on the existing Stata procedure metan which is typically used to pool effects (risk ratios, odds ratios, differences of risks or means) but which is also used to pool proportions. Metaprop implements procedures which are specific to binomial data and allows computation of exact binomial and score test-based confidence intervals. It provides appropriate methods for dealing with proportions close to or at the margins where the normal approximation procedures often break down, by use of the binomial distribution to model the within-study variability or by allowing Freeman-Tukey double arcsine transformation to stabilize the variances. Metaprop was applied on two published meta-analyses: 1) prevalence of HPV-infection in women with a Pap smear showing ASC-US; 2) cure rate after treatment for cervical precancer using cold coagulation. The first meta-analysis showed a pooled HPV-prevalence of 43% (95% CI: 38%-48%). In the second meta-analysis, the pooled percentage of cured women was 94% (95% CI: 86%-97%). By using metaprop, no studies with 0% or 100% proportions were excluded from the meta-analysis. Furthermore, study specific and pooled confidence intervals always were within admissible values, contrary to the original publication, where metan was used.
Homeopathy: meta-analyses of pooled clinical data.
Hahn, Robert G
2013-01-01
In the first decade of the evidence-based era, which began in the mid-1990s, meta-analyses were used to scrutinize homeopathy for evidence of beneficial effects in medical conditions. In this review, meta-analyses including pooled data from placebo-controlled clinical trials of homeopathy and the aftermath in the form of debate articles were analyzed. In 1997 Klaus Linde and co-workers identified 89 clinical trials that showed an overall odds ratio of 2.45 in favor of homeopathy over placebo. There was a trend toward smaller benefit from studies of the highest quality, but the 10 trials with the highest Jadad score still showed homeopathy had a statistically significant effect. These results challenged academics to perform alternative analyses that, to demonstrate the lack of effect, relied on extensive exclusion of studies, often to the degree that conclusions were based on only 5-10% of the material, or on virtual data. The ultimate argument against homeopathy is the 'funnel plot' published by Aijing Shang's research group in 2005. However, the funnel plot is flawed when applied to a mixture of diseases, because studies with expected strong treatments effects are, for ethical reasons, powered lower than studies with expected weak or unclear treatment effects. To conclude that homeopathy lacks clinical effect, more than 90% of the available clinical trials had to be disregarded. Alternatively, flawed statistical methods had to be applied. Future meta-analyses should focus on the use of homeopathy in specific diseases or groups of diseases instead of pooling data from all clinical trials. © 2013 S. Karger GmbH, Freiburg.
BRepertoire: a user-friendly web server for analysing antibody repertoire data.
Margreitter, Christian; Lu, Hui-Chun; Townsend, Catherine; Stewart, Alexander; Dunn-Walters, Deborah K; Fraternali, Franca
2018-04-14
Antibody repertoire analysis by high throughput sequencing is now widely used, but a persisting challenge is enabling immunologists to explore their data to discover discriminating repertoire features for their own particular investigations. Computational methods are necessary for large-scale evaluation of antibody properties. We have developed BRepertoire, a suite of user-friendly web-based software tools for large-scale statistical analyses of repertoire data. The software is able to use data preprocessed by IMGT, and performs statistical and comparative analyses with versatile plotting options. BRepertoire has been designed to operate in various modes, for example analysing sequence-specific V(D)J gene usage, discerning physico-chemical properties of the CDR regions and clustering of clonotypes. Those analyses are performed on the fly by a number of R packages and are deployed by a shiny web platform. The user can download the analysed data in different table formats and save the generated plots as image files ready for publication. We believe BRepertoire to be a versatile analytical tool that complements experimental studies of immune repertoires. To illustrate the server's functionality, we show use cases including differential gene usage in a vaccination dataset and analysis of CDR3H properties in old and young individuals. The server is accessible under http://mabra.biomed.kcl.ac.uk/BRepertoire.
Study/experimental/research design: much more than statistics.
Knight, Kenneth L
2010-01-01
The purpose of study, experimental, or research design in scientific manuscripts has changed significantly over the years. It has evolved from an explanation of the design of the experiment (ie, data gathering or acquisition) to an explanation of the statistical analysis. This practice makes "Methods" sections hard to read and understand. To clarify the difference between study design and statistical analysis, to show the advantages of a properly written study design on article comprehension, and to encourage authors to correctly describe study designs. The role of study design is explored from the introduction of the concept by Fisher through modern-day scientists and the AMA Manual of Style. At one time, when experiments were simpler, the study design and statistical design were identical or very similar. With the complex research that is common today, which often includes manipulating variables to create new variables and the multiple (and different) analyses of a single data set, data collection is very different than statistical design. Thus, both a study design and a statistical design are necessary. Scientific manuscripts will be much easier to read and comprehend. A proper experimental design serves as a road map to the study methods, helping readers to understand more clearly how the data were obtained and, therefore, assisting them in properly analyzing the results.
Egbewale, Bolaji E; Lewis, Martyn; Sim, Julius
2014-04-09
Analysis of variance (ANOVA), change-score analysis (CSA) and analysis of covariance (ANCOVA) respond differently to baseline imbalance in randomized controlled trials. However, no empirical studies appear to have quantified the differential bias and precision of estimates derived from these methods of analysis, and their relative statistical power, in relation to combinations of levels of key trial characteristics. This simulation study therefore examined the relative bias, precision and statistical power of these three analyses using simulated trial data. 126 hypothetical trial scenarios were evaluated (126,000 datasets), each with continuous data simulated by using a combination of levels of: treatment effect; pretest-posttest correlation; direction and magnitude of baseline imbalance. The bias, precision and power of each method of analysis were calculated for each scenario. Compared to the unbiased estimates produced by ANCOVA, both ANOVA and CSA are subject to bias, in relation to pretest-posttest correlation and the direction of baseline imbalance. Additionally, ANOVA and CSA are less precise than ANCOVA, especially when pretest-posttest correlation ≥ 0.3. When groups are balanced at baseline, ANCOVA is at least as powerful as the other analyses. Apparently greater power of ANOVA and CSA at certain imbalances is achieved in respect of a biased treatment effect. Across a range of correlations between pre- and post-treatment scores and at varying levels and direction of baseline imbalance, ANCOVA remains the optimum statistical method for the analysis of continuous outcomes in RCTs, in terms of bias, precision and statistical power.
2014-01-01
Background Analysis of variance (ANOVA), change-score analysis (CSA) and analysis of covariance (ANCOVA) respond differently to baseline imbalance in randomized controlled trials. However, no empirical studies appear to have quantified the differential bias and precision of estimates derived from these methods of analysis, and their relative statistical power, in relation to combinations of levels of key trial characteristics. This simulation study therefore examined the relative bias, precision and statistical power of these three analyses using simulated trial data. Methods 126 hypothetical trial scenarios were evaluated (126 000 datasets), each with continuous data simulated by using a combination of levels of: treatment effect; pretest-posttest correlation; direction and magnitude of baseline imbalance. The bias, precision and power of each method of analysis were calculated for each scenario. Results Compared to the unbiased estimates produced by ANCOVA, both ANOVA and CSA are subject to bias, in relation to pretest-posttest correlation and the direction of baseline imbalance. Additionally, ANOVA and CSA are less precise than ANCOVA, especially when pretest-posttest correlation ≥ 0.3. When groups are balanced at baseline, ANCOVA is at least as powerful as the other analyses. Apparently greater power of ANOVA and CSA at certain imbalances is achieved in respect of a biased treatment effect. Conclusions Across a range of correlations between pre- and post-treatment scores and at varying levels and direction of baseline imbalance, ANCOVA remains the optimum statistical method for the analysis of continuous outcomes in RCTs, in terms of bias, precision and statistical power. PMID:24712304
Psychophysiological investigations of the biomedical problems of manned spaceflight
NASA Technical Reports Server (NTRS)
1993-01-01
The Final Report on psychophysiological investigations of the biomedical problems of manned spaceflight is presented. In the first project, statistical analyses of human autonomic data were performed. The objectives were the following: to establish a relational data base containing human psychophysiological data obtained from Shuttle flight experiments and ground-based research over a 20 year period; to enable multi-user access and retrieval of these data for subsequent analyses and for possible inclusion in the proposed Life Sciences Data Archive; and to enable/conduct statistical analyses across several experiments on large subject populations which can thereby provide definitive answers to questions on human autonomic and behavioral responses and adaptation to environmental stressors on Earth and in space. The second project studied motion sickness. The objectives were: to test/develop hardware and procedures to be incorporated into preflight training of crewmembers of Spacelab-J; and to examine spin-off applications of AFT. The third project studied orthostatic intolerance. The objective was to test the feasibility of applying autogenic-feedback training as a potential treatment for postflight orthostatic intolerance.
Spedding, Simon
2014-04-11
Efficacy of Vitamin D supplements in depression is controversial, awaiting further literature analysis. Biological flaws in primary studies is a possible reason meta-analyses of Vitamin D have failed to demonstrate efficacy. This systematic review and meta-analysis of Vitamin D and depression compared studies with and without biological flaws. The systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The literature search was undertaken through four databases for randomized controlled trials (RCTs). Studies were critically appraised for methodological quality and biological flaws, in relation to the hypothesis and study design. Meta-analyses were performed for studies according to the presence of biological flaws. The 15 RCTs identified provide a more comprehensive evidence-base than previous systematic reviews; methodological quality of studies was generally good and methodology was diverse. A meta-analysis of all studies without flaws demonstrated a statistically significant improvement in depression with Vitamin D supplements (+0.78 CI +0.24, +1.27). Studies with biological flaws were mainly inconclusive, with the meta-analysis demonstrating a statistically significant worsening in depression by taking Vitamin D supplements (-1.1 CI -0.7, -1.5). Vitamin D supplementation (≥800 I.U. daily) was somewhat favorable in the management of depression in studies that demonstrate a change in vitamin levels, and the effect size was comparable to that of anti-depressant medication.
Drivers willingness to pay progressive rate for street parking.
DOT National Transportation Integrated Search
2015-01-01
This study finds willingness to pay and price elasticity for on-street parking demand using stated : preference data obtained from 238 respondents. Descriptive, statistical and economic analyses including : regression, generalized linear model, and f...
Evaluating Research Articles from Start to Finish.
ERIC Educational Resources Information Center
Girden, Ellen R.
This book in intended to train students in reading a research report critically. It uses actual research articles as examples including both good and flawed studies in each category and provides interpretation and evaluation of the appropriateness of the statistical analyses in each study. Individual chapters usually include two sample studies and…
77 FR 75414 - Submission for OMB Review; Comment Request
Federal Register 2010, 2011, 2012, 2013, 2014
2012-12-20
... conduct non-DoDEA sponsored research studies in DoDEA schools, districts, and/ or areas. The DoDEA Form 2071.3-F1, ``Research Study Request'' collects information about the researcher, the research project, audience, timeline, and the statistical analyses that will be conducted during the proposed research study...
Vleeshouwers, Jolien; Knardahl, Stein; Christensen, Jan Olav
2016-04-01
This prospective cohort study examined previously underexplored relations between psychological/social work factors and troubled sleep in order to provide practical information about specific, modifiable factors at work. A comprehensive evaluation of a range of psychological/social work factors was obtained by several designs; i.e., cross-sectional analyses at baseline and follow-up, prospective analyses with baseline predictors (T1), prospective analyses with average exposure across waves as predictor ([T1 + T2] / 2), and prospective analyses with change in exposure from baseline to follow-up as predictor. Participants consisted of a sample of Norwegian employees from a broad spectrum of occupations, who completed a questionnaire at two points in time, approximately two years apart. Cross-sectional analyses at T1 comprised 7,459 participants, cross-sectional analyses at T2 included 6,688 participants. Prospective analyses comprised a sample 5,070 of participants who responded at both T1 and T2. Univariable and multivariable ordinal logistic regressions were performed. Thirteen psychological/social work factors and two aspects of troubled sleep, namely difficulties initiating sleep and disturbed sleep, were studied. Ordinal logistic regressions revealed statistically significant associations for all psychological and social work factors in at least one of the analyses. Psychological and social work factors predicted sleep problems in the short term as well as the long term. All work factors investigated showed statistically significant associations with both sleep items, however quantitative job demands, decision control, role conflict, and support from superior were the most robust predictors and may therefore be suitable targets of interventions aimed at improving employee sleep. © 2016 Associated Professional Sleep Societies, LLC.
Ethnic/racial misidentification in death: a problem which may distort suicide statistics.
Andres, V R
1977-01-01
Since the majority of suicide studies are ex post facto studies of demographic data collected by pathologists anc coroner's investigators, the role of the forensic scientist in determining the accuracy of statistical analyses of death is extremely important. This paper discusses how two salient features of a decedent, surname and residence location, can be misleading in determining the ethnic/racial classification of the decreased. Because many Southern California Indians have Spanish Surnames and most do not reside on an Indian reservation it is shown that the suicide statistics may represent an over-estimation of actual Mexican-American suicidal deaths while simultaneously representing an under-estimation of the suicides among American Indians of the region.
Computing Inter-Rater Reliability for Observational Data: An Overview and Tutorial
Hallgren, Kevin A.
2012-01-01
Many research designs require the assessment of inter-rater reliability (IRR) to demonstrate consistency among observational ratings provided by multiple coders. However, many studies use incorrect statistical procedures, fail to fully report the information necessary to interpret their results, or do not address how IRR affects the power of their subsequent analyses for hypothesis testing. This paper provides an overview of methodological issues related to the assessment of IRR with a focus on study design, selection of appropriate statistics, and the computation, interpretation, and reporting of some commonly-used IRR statistics. Computational examples include SPSS and R syntax for computing Cohen’s kappa and intra-class correlations to assess IRR. PMID:22833776
NASA Astrophysics Data System (ADS)
Amat, Arnau; Zapata, Corinna; Alexakos, Konstantinos; Pride, Leah D.; Paylor-Smith, Christian; Hernandez, Matthew
2016-09-01
In this paper, we look closely at two events selected through event-oriented inquiry that were part of a classroom presentation on race. The first event was a provocative discussion about Mark Twain's ( Pudd'nhead Wilson, Harper, New York, 1899) and passing for being White. The other was a discussion on the use of the N-word. Grounded in authentic inquiry, we use ethnographic narrative, cogenerative dialogues, and video and oximeter data analyses as part of a multi-ontological approach for studying emotions. Statistical analysis of oximeter data shows statistically significant heart rate synchrony among two of the coteachers during their presentations, providing evidence of emotional synchrony, resonance, and social and emotional contagion.
Inelastic Single Pion Signal Study in T2K νe Appearance using Modified Decay Electron Cut
NASA Astrophysics Data System (ADS)
Iwamoto, Konosuke; T2K Collaboration
2015-04-01
The T2K long-baseline neutrino experiment uses sophisticated selection criteria to identify the neutrino oscillation signals among the events reconstructed in the Super-Kamiokande (SK) detector for νe and νμ appearance and disappearance analyses. In current analyses, charged-current quasi-elastic (CCQE) events are used as the signal reaction in the SK detector because the energy can be precisely reconstructed. This talk presents an approach to increase the statistics of the oscillation analysis by including non-CCQE events with one Michel electron and reconstruct them as the inelastic single pion productions. The increase in statistics, backgrounds to this new process and energy reconstruction implications will be presented with this increased event sample.
Kent, David M; Dahabreh, Issa J; Ruthazer, Robin; Furlan, Anthony J; Weimar, Christian; Serena, Joaquín; Meier, Bernhard; Mattle, Heinrich P; Di Angelantonio, Emanuele; Paciaroni, Maurizio; Schuchlenz, Herwig; Homma, Shunichi; Lutz, Jennifer S; Thaler, David E
2015-09-14
The preferred antithrombotic strategy for secondary prevention in patients with cryptogenic stroke (CS) and patent foramen ovale (PFO) is unknown. We pooled multiple observational studies and used propensity score-based methods to estimate the comparative effectiveness of oral anticoagulation (OAC) compared with antiplatelet therapy (APT). Individual participant data from 12 databases of medically treated patients with CS and PFO were analysed with Cox regression models, to estimate database-specific hazard ratios (HRs) comparing OAC with APT, for both the primary composite outcome [recurrent stroke, transient ischaemic attack (TIA), or death] and stroke alone. Propensity scores were applied via inverse probability of treatment weighting to control for confounding. We synthesized database-specific HRs using random-effects meta-analysis models. This analysis included 2385 (OAC = 804 and APT = 1581) patients with 227 composite endpoints (stroke/TIA/death). The difference between OAC and APT was not statistically significant for the primary composite outcome [adjusted HR = 0.76, 95% confidence interval (CI) 0.52-1.12] or for the secondary outcome of stroke alone (adjusted HR = 0.75, 95% CI 0.44-1.27). Results were consistent in analyses applying alternative weighting schemes, with the exception that OAC had a statistically significant beneficial effect on the composite outcome in analyses standardized to the patient population who actually received APT (adjusted HR = 0.64, 95% CI 0.42-0.99). Subgroup analyses did not detect statistically significant heterogeneity of treatment effects across clinically important patient groups. We did not find a statistically significant difference comparing OAC with APT; our results justify randomized trials comparing different antithrombotic approaches in these patients. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2015. For permissions please email: journals.permissions@oup.com.
Chaisinanunkul, Napasri; Adeoye, Opeolu; Lewis, Roger J.; Grotta, James C.; Broderick, Joseph; Jovin, Tudor G.; Nogueira, Raul G.; Elm, Jordan; Graves, Todd; Berry, Scott; Lees, Kennedy R.; Barreto, Andrew D.; Saver, Jeffrey L.
2015-01-01
Background and Purpose Although the modified Rankin Scale (mRS) is the most commonly employed primary endpoint in acute stroke trials, its power is limited when analyzed in dichotomized fashion and its indication of effect size challenging to interpret when analyzed ordinally. Weighting the seven Rankin levels by utilities may improve scale interpretability while preserving statistical power. Methods A utility weighted mRS (UW-mRS) was derived by averaging values from time-tradeoff (patient centered) and person-tradeoff (clinician centered) studies. The UW-mRS, standard ordinal mRS, and dichotomized mRS were applied to 11 trials or meta-analyses of acute stroke treatments, including lytic, endovascular reperfusion, blood pressure moderation, and hemicraniectomy interventions. Results Utility values were: mRS 0–1.0; mRS 1 - 0.91; mRS 2 - 0.76; mRS 3 - 0.65; mRS 4 - 0.33; mRS 5 & 6 - 0. For trials with unidirectional treatment effects, the UW-mRS paralleled the ordinal mRS and outperformed dichotomous mRS analyses. Both the UW-mRS and the ordinal mRS were statistically significant in six of eight unidirectional effect trials, while dichotomous analyses were statistically significant in two to four of eight. In bidirectional effect trials, both the UW-mRS and ordinal tests captured the divergent treatment effects by showing neutral results whereas some dichotomized analyses showed positive results. Mean utility differences in trials with statistically significant positive results ranged from 0.026 to 0.249. Conclusion A utility-weighted mRS performs similarly to the standard ordinal mRS in detecting treatment effects in actual stroke trials and ensures the quantitative outcome is a valid reflection of patient-centered benefits. PMID:26138130
Using Meta-analyses for Comparative Effectiveness Research
Ruppar, Todd M.; Phillips, Lorraine J.; Chase, Jo-Ana D.
2012-01-01
Comparative effectiveness research seeks to identify the most effective interventions for particular patient populations. Meta-analysis is an especially valuable form of comparative effectiveness research because it emphasizes the magnitude of intervention effects rather than relying on tests of statistical significance among primary studies. Overall effects can be calculated for diverse clinical and patient-centered variables to determine the outcome patterns. Moderator analyses compare intervention characteristics among primary studies by determining if effect sizes vary among studies with different intervention characteristics. Intervention effectiveness can be linked to patient characteristics to provide evidence for patient-centered care. Moderator analyses often answer questions never posed by primary studies because neither multiple intervention characteristics nor populations are compared in single primary studies. Thus meta-analyses provide unique contributions to knowledge. Although meta-analysis is a powerful comparative effectiveness strategy, methodological challenges and limitations in primary research must be acknowledged to interpret findings. PMID:22789450
Trutschel, Diana; Palm, Rebecca; Holle, Bernhard; Simon, Michael
2017-11-01
Because not every scientific question on effectiveness can be answered with randomised controlled trials, research methods that minimise bias in observational studies are required. Two major concerns influence the internal validity of effect estimates: selection bias and clustering. Hence, to reduce the bias of the effect estimates, more sophisticated statistical methods are needed. To introduce statistical approaches such as propensity score matching and mixed models into representative real-world analysis and to conduct the implementation in statistical software R to reproduce the results. Additionally, the implementation in R is presented to allow the results to be reproduced. We perform a two-level analytic strategy to address the problems of bias and clustering: (i) generalised models with different abilities to adjust for dependencies are used to analyse binary data and (ii) the genetic matching and covariate adjustment methods are used to adjust for selection bias. Hence, we analyse the data from two population samples, the sample produced by the matching method and the full sample. The different analysis methods in this article present different results but still point in the same direction. In our example, the estimate of the probability of receiving a case conference is higher in the treatment group than in the control group. Both strategies, genetic matching and covariate adjustment, have their limitations but complement each other to provide the whole picture. The statistical approaches were feasible for reducing bias but were nevertheless limited by the sample used. For each study and obtained sample, the pros and cons of the different methods have to be weighted. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.
McLawhorn, Alexander S; Steinhaus, Michael E; Southren, Daniel L; Lee, Yuo-Yu; Dodwell, Emily R; Figgie, Mark P
2017-01-01
The purpose of this study was to compare the health-related quality of life (HRQoL) of patients across World Health Organization (WHO) body mass index (BMI) classes before and after total hip arthroplasty (THA). Patients with end-stage hip osteoarthritis who received elective primary unilateral THA were identified through an institutional registry and categorized based on the World Health Organization BMI classification. Age, sex, laterality, year of surgery, and Charlson-Deyo comorbidity index were recorded. The primary outcome was the EQ-5D-3L index and visual analog scale (EQ-VAS) scores at 2 years postoperatively. Inferential statistics and regression analyses were performed to determine associations between BMI classes and HRQoL. EQ-5D-3L scores at baseline and at 2 years were statistically different across BMI classes, with higher EQ-VAS and index scores in patients with lower BMI. There was no difference observed for the 2-year change in EQ-VAS scores, but there was a statistically greater increase in index scores for more obese patients. In the regression analyses, there were statistically significant negative effect estimates for EQ-VAS and index scores associated with increasing BMI class. BMI class is independently associated with lower HRQoL scores 2 years after primary THA. While absolute scores in obese patients were lower than in nonobese patients, obese patients enjoyed more positive changes in EQ-5D index scores after THA. These results may provide the most detailed information on how BMI influences HRQoL before and after THA, and they are relevant to future economic decision analyses on the topic. Copyright © 2016 Elsevier Inc. All rights reserved.
Rhodes, Kirsty M; Turner, Rebecca M; White, Ian R; Jackson, Dan; Spiegelhalter, David J; Higgins, Julian P T
2016-12-20
Many meta-analyses combine results from only a small number of studies, a situation in which the between-study variance is imprecisely estimated when standard methods are applied. Bayesian meta-analysis allows incorporation of external evidence on heterogeneity, providing the potential for more robust inference on the effect size of interest. We present a method for performing Bayesian meta-analysis using data augmentation, in which we represent an informative conjugate prior for between-study variance by pseudo data and use meta-regression for estimation. To assist in this, we derive predictive inverse-gamma distributions for the between-study variance expected in future meta-analyses. These may serve as priors for heterogeneity in new meta-analyses. In a simulation study, we compare approximate Bayesian methods using meta-regression and pseudo data against fully Bayesian approaches based on importance sampling techniques and Markov chain Monte Carlo (MCMC). We compare the frequentist properties of these Bayesian methods with those of the commonly used frequentist DerSimonian and Laird procedure. The method is implemented in standard statistical software and provides a less complex alternative to standard MCMC approaches. An importance sampling approach produces almost identical results to standard MCMC approaches, and results obtained through meta-regression and pseudo data are very similar. On average, data augmentation provides closer results to MCMC, if implemented using restricted maximum likelihood estimation rather than DerSimonian and Laird or maximum likelihood estimation. The methods are applied to real datasets, and an extension to network meta-analysis is described. The proposed method facilitates Bayesian meta-analysis in a way that is accessible to applied researchers. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.
Statistical Design Model (SDM) of satellite thermal control subsystem
NASA Astrophysics Data System (ADS)
Mirshams, Mehran; Zabihian, Ehsan; Aarabi Chamalishahi, Mahdi
2016-07-01
Satellites thermal control, is a satellite subsystem that its main task is keeping the satellite components at its own survival and activity temperatures. Ability of satellite thermal control plays a key role in satisfying satellite's operational requirements and designing this subsystem is a part of satellite design. In the other hand due to the lack of information provided by companies and designers still doesn't have a specific design process while it is one of the fundamental subsystems. The aim of this paper, is to identify and extract statistical design models of spacecraft thermal control subsystem by using SDM design method. This method analyses statistical data with a particular procedure. To implement SDM method, a complete database is required. Therefore, we first collect spacecraft data and create a database, and then we extract statistical graphs using Microsoft Excel, from which we further extract mathematical models. Inputs parameters of the method are mass, mission, and life time of the satellite. For this purpose at first thermal control subsystem has been introduced and hardware using in the this subsystem and its variants has been investigated. In the next part different statistical models has been mentioned and a brief compare will be between them. Finally, this paper particular statistical model is extracted from collected statistical data. Process of testing the accuracy and verifying the method use a case study. Which by the comparisons between the specifications of thermal control subsystem of a fabricated satellite and the analyses results, the methodology in this paper was proved to be effective. Key Words: Thermal control subsystem design, Statistical design model (SDM), Satellite conceptual design, Thermal hardware
Edjabou, Maklawe Essonanawe; Martín-Fernández, Josep Antoni; Scheutz, Charlotte; Astrup, Thomas Fruergaard
2017-11-01
Data for fractional solid waste composition provide relative magnitudes of individual waste fractions, the percentages of which always sum to 100, thereby connecting them intrinsically. Due to this sum constraint, waste composition data represent closed data, and their interpretation and analysis require statistical methods, other than classical statistics that are suitable only for non-constrained data such as absolute values. However, the closed characteristics of waste composition data are often ignored when analysed. The results of this study showed, for example, that unavoidable animal-derived food waste amounted to 2.21±3.12% with a confidence interval of (-4.03; 8.45), which highlights the problem of the biased negative proportions. A Pearson's correlation test, applied to waste fraction generation (kg mass), indicated a positive correlation between avoidable vegetable food waste and plastic packaging. However, correlation tests applied to waste fraction compositions (percentage values) showed a negative association in this regard, thus demonstrating that statistical analyses applied to compositional waste fraction data, without addressing the closed characteristics of these data, have the potential to generate spurious or misleading results. Therefore, ¨compositional data should be transformed adequately prior to any statistical analysis, such as computing mean, standard deviation and correlation coefficients. Copyright © 2017 Elsevier Ltd. All rights reserved.
Predictors of persistent pain after total knee arthroplasty: a systematic review and meta-analysis.
Lewis, G N; Rice, D A; McNair, P J; Kluger, M
2015-04-01
Several studies have identified clinical, psychosocial, patient characteristic, and perioperative variables that are associated with persistent postsurgical pain; however, the relative effect of these variables has yet to be quantified. The aim of the study was to provide a systematic review and meta-analysis of predictor variables associated with persistent pain after total knee arthroplasty (TKA). Included studies were required to measure predictor variables prior to or at the time of surgery, include a pain outcome measure at least 3 months post-TKA, and include a statistical analysis of the effect of the predictor variable(s) on the outcome measure. Counts were undertaken of the number of times each predictor was analysed and the number of times it was found to have a significant relationship with persistent pain. Separate meta-analyses were performed to determine the effect size of each predictor on persistent pain. Outcomes from studies implementing uni- and multivariable statistical models were analysed separately. Thirty-two studies involving almost 30 000 patients were included in the review. Preoperative pain was the predictor that most commonly demonstrated a significant relationship with persistent pain across uni- and multivariable analyses. In the meta-analyses of data from univariate models, the largest effect sizes were found for: other pain sites, catastrophizing, and depression. For data from multivariate models, significant effects were evident for: catastrophizing, preoperative pain, mental health, and comorbidities. Catastrophizing, mental health, preoperative knee pain, and pain at other sites are the strongest independent predictors of persistent pain after TKA. © The Author 2014. Published by Oxford University Press on behalf of the British Journal of Anaesthesia. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Statistical Evaluation of Molecular Contamination During Spacecraft Thermal Vacuum Test
NASA Technical Reports Server (NTRS)
Chen, Philip; Hedgeland, Randy; Montoya, Alex; Roman-Velazquez, Juan; Dunn, Jamie; Colony, Joe; Petitto, Joseph
1998-01-01
The purpose of this paper is to evaluate the statistical molecular contamination data with a goal to improve spacecraft contamination control. The statistical data was generated in typical thermal vacuum tests at the National Aeronautics and Space Administration, Goddard Space Flight Center (GSFC). The magnitude of material outgassing was measured using a Quartz Crystal Microbalance (QCM) device during the test. A solvent rinse sample was taken at the conclusion of each test. Then detailed qualitative and quantitative measurements were obtained through chemical analyses. All data used in this study encompassed numerous spacecraft tests in recent years.
Statistical Evaluation of Molecular Contamination During Spacecraft Thermal Vacuum Test
NASA Technical Reports Server (NTRS)
Chen, Philip; Hedgeland, Randy; Montoya, Alex; Roman-Velazquez, Juan; Dunn, Jamie; Colony, Joe; Petitto, Joseph
1999-01-01
The purpose of this paper is to evaluate the statistical molecular contamination data with a goal to improve spacecraft contamination control. The statistical data was generated in typical thermal vacuum tests at the National Aeronautics and Space Administration, Goddard Space Flight Center (GSFC). The magnitude of material outgassing was measured using a Quartz Crystal Microbalance (QCNO device during the test. A solvent rinse sample was taken at the conclusion of each test. Then detailed qualitative and quantitative measurements were obtained through chemical analyses. All data used in this study encompassed numerous spacecraft tests in recent years.
Statistical Evaluation of Molecular Contamination During Spacecraft Thermal Vacuum Test
NASA Technical Reports Server (NTRS)
Chen, Philip; Hedgeland, Randy; Montoya, Alex; Roman-Velazquez, Juan; Dunn, Jamie; Colony, Joe; Petitto, Joseph
1997-01-01
The purpose of this paper is to evaluate the statistical molecular contamination data with a goal to improve spacecraft contamination control. The statistical data was generated in typical thermal vacuum tests at the National Aeronautics and Space Administration, Goddard Space Flight Center (GSFC). The magnitude of material outgassing was measured using a Quartz Crystal Microbalance (QCM) device during the test. A solvent rinse sample was taken at the conclusion of the each test. Then detailed qualitative and quantitative measurements were obtained through chemical analyses. All data used in this study encompassed numerous spacecraft tests in recent years.
NASA Astrophysics Data System (ADS)
Clerc, F.; Njiki-Menga, G.-H.; Witschger, O.
2013-04-01
Most of the measurement strategies that are suggested at the international level to assess workplace exposure to nanomaterials rely on devices measuring, in real time, airborne particles concentrations (according different metrics). Since none of the instruments to measure aerosols can distinguish a particle of interest to the background aerosol, the statistical analysis of time resolved data requires special attention. So far, very few approaches have been used for statistical analysis in the literature. This ranges from simple qualitative analysis of graphs to the implementation of more complex statistical models. To date, there is still no consensus on a particular approach and the current period is always looking for an appropriate and robust method. In this context, this exploratory study investigates a statistical method to analyse time resolved data based on a Bayesian probabilistic approach. To investigate and illustrate the use of the this statistical method, particle number concentration data from a workplace study that investigated the potential for exposure via inhalation from cleanout operations by sandpapering of a reactor producing nanocomposite thin films have been used. In this workplace study, the background issue has been addressed through the near-field and far-field approaches and several size integrated and time resolved devices have been used. The analysis of the results presented here focuses only on data obtained with two handheld condensation particle counters. While one was measuring at the source of the released particles, the other one was measuring in parallel far-field. The Bayesian probabilistic approach allows a probabilistic modelling of data series, and the observed task is modelled in the form of probability distributions. The probability distributions issuing from time resolved data obtained at the source can be compared with the probability distributions issuing from the time resolved data obtained far-field, leading in a quantitative estimation of the airborne particles released at the source when the task is performed. Beyond obtained results, this exploratory study indicates that the analysis of the results requires specific experience in statistics.
Binny, Diana; Mezzenga, Emilio; Lancaster, Craig M; Trapp, Jamie V; Kairn, Tanya; Crowe, Scott B
2017-06-01
The aims of this study were to investigate machine beam parameters using the TomoTherapy quality assurance (TQA) tool, establish a correlation to patient delivery quality assurance results and to evaluate the relationship between energy variations detected using different TQA modules. TQA daily measurement results from two treatment machines for periods of up to 4years were acquired. Analyses of beam quality, helical and static output variations were made. Variations from planned dose were also analysed using Statistical Process Control (SPC) technique and their relationship to output trends were studied. Energy variations appeared to be one of the contributing factors to delivery output dose seen in the analysis. Ion chamber measurements were reliable indicators of energy and output variations and were linear with patient dose verifications. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.
Rubio-Aparicio, María; Sánchez-Meca, Julio; López-López, José Antonio; Botella, Juan; Marín-Martínez, Fulgencio
2017-11-01
Subgroup analyses allow us to examine the influence of a categorical moderator on the effect size in meta-analysis. We conducted a simulation study using a dichotomous moderator, and compared the impact of pooled versus separate estimates of the residual between-studies variance on the statistical performance of the Q B (P) and Q B (S) tests for subgroup analyses assuming a mixed-effects model. Our results suggested that similar performance can be expected as long as there are at least 20 studies and these are approximately balanced across categories. Conversely, when subgroups were unbalanced, the practical consequences of having heterogeneous residual between-studies variances were more evident, with both tests leading to the wrong statistical conclusion more often than in the conditions with balanced subgroups. A pooled estimate should be preferred for most scenarios, unless the residual between-studies variances are clearly different and there are enough studies in each category to obtain precise separate estimates. © 2017 The British Psychological Society.
Plant selection for ethnobotanical uses on the Amalfi Coast (Southern Italy).
Savo, V; Joy, R; Caneva, G; McClatchey, W C
2015-07-15
Many ethnobotanical studies have investigated selection criteria for medicinal and non-medicinal plants. In this paper we test several statistical methods using different ethnobotanical datasets in order to 1) define to which extent the nature of the datasets can affect the interpretation of results; 2) determine if the selection for different plant uses is based on phylogeny, or other selection criteria. We considered three different ethnobotanical datasets: two datasets of medicinal plants and a dataset of non-medicinal plants (handicraft production, domestic and agro-pastoral practices) and two floras of the Amalfi Coast. We performed residual analysis from linear regression, the binomial test and the Bayesian approach for calculating under-used and over-used plant families within ethnobotanical datasets. Percentages of agreement were calculated to compare the results of the analyses. We also analyzed the relationship between plant selection and phylogeny, chorology, life form and habitat using the chi-square test. Pearson's residuals for each of the significant chi-square analyses were examined for investigating alternative hypotheses of plant selection criteria. The three statistical analysis methods differed within the same dataset, and between different datasets and floras, but with some similarities. In the two medicinal datasets, only Lamiaceae was identified in both floras as an over-used family by all three statistical methods. All statistical methods in one flora agreed that Malvaceae was over-used and Poaceae under-used, but this was not found to be consistent with results of the second flora in which one statistical result was non-significant. All other families had some discrepancy in significance across methods, or floras. Significant over- or under-use was observed in only a minority of cases. The chi-square analyses were significant for phylogeny, life form and habitat. Pearson's residuals indicated a non-random selection of woody species for non-medicinal uses and an under-use of plants of temperate forests for medicinal uses. Our study showed that selection criteria for plant uses (including medicinal) are not always based on phylogeny. The comparison of different statistical methods (regression, binomial and Bayesian) under different conditions led to the conclusion that the most conservative results are obtained using regression analysis.
Social Early Stimulation of Trisomy-21 Babies
ERIC Educational Resources Information Center
Aparicio, Maria Teresa Sanz; Balana, Javier Menendez
2003-01-01
This study was initiated with twenty Down's syndrome babies to verify whether subjects undergoing social early stimulation would benefit from this type of treatment. An experimental study was designed with two training groups: visual or written instructions. The analyses of the results established statistically significant differences in the…
21 CFR 314.50 - Content and format of an application.
Code of Federal Regulations, 2013 CFR
2013-04-01
... the protocol and a description of the statistical analyses used to evaluate the study. If the study... application: (i) Three copies of the analytical procedures and related descriptive information contained in... the samples and to validate the applicant's analytical procedures. The related descriptive information...
21 CFR 314.50 - Content and format of an application.
Code of Federal Regulations, 2012 CFR
2012-04-01
... the protocol and a description of the statistical analyses used to evaluate the study. If the study... application: (i) Three copies of the analytical procedures and related descriptive information contained in... the samples and to validate the applicant's analytical procedures. The related descriptive information...
21 CFR 314.50 - Content and format of an application.
Code of Federal Regulations, 2014 CFR
2014-04-01
... the protocol and a description of the statistical analyses used to evaluate the study. If the study... application: (i) Three copies of the analytical procedures and related descriptive information contained in... the samples and to validate the applicant's analytical procedures. The related descriptive information...
21 CFR 314.50 - Content and format of an application.
Code of Federal Regulations, 2011 CFR
2011-04-01
... the protocol and a description of the statistical analyses used to evaluate the study. If the study... application: (i) Three copies of the analytical procedures and related descriptive information contained in... the samples and to validate the applicant's analytical procedures. The related descriptive information...
21 CFR 314.50 - Content and format of an application.
Code of Federal Regulations, 2010 CFR
2010-04-01
... the protocol and a description of the statistical analyses used to evaluate the study. If the study... application: (i) Three copies of the analytical procedures and related descriptive information contained in... the samples and to validate the applicant's analytical procedures. The related descriptive information...
Using Markov Chain Analyses in Counselor Education Research
ERIC Educational Resources Information Center
Duys, David K.; Headrick, Todd C.
2004-01-01
This study examined the efficacy of an infrequently used statistical analysis in counselor education research. A Markov chain analysis was used to examine hypothesized differences between students' use of counseling skills in an introductory course. Thirty graduate students participated in the study. Independent raters identified the microskills…
Ho, Andrew D; Yu, Carol C
2015-06-01
Many statistical analyses benefit from the assumption that unconditional or conditional distributions are continuous and normal. More than 50 years ago in this journal, Lord and Cook chronicled departures from normality in educational tests, and Micerri similarly showed that the normality assumption is met rarely in educational and psychological practice. In this article, the authors extend these previous analyses to state-level educational test score distributions that are an increasingly common target of high-stakes analysis and interpretation. Among 504 scale-score and raw-score distributions from state testing programs from recent years, nonnormal distributions are common and are often associated with particular state programs. The authors explain how scaling procedures from item response theory lead to nonnormal distributions as well as unusual patterns of discreteness. The authors recommend that distributional descriptive statistics be calculated routinely to inform model selection for large-scale test score data, and they illustrate consequences of nonnormality using sensitivity studies that compare baseline results to those from normalized score scales.
Statistical analysis of the determinations of the Sun's Galactocentric distance
NASA Astrophysics Data System (ADS)
Malkin, Zinovy
2013-02-01
Based on several tens of R0 measurements made during the past two decades, several studies have been performed to derive the best estimate of R0. Some used just simple averaging to derive a result, whereas others provided comprehensive analyses of possible errors in published results. In either case, detailed statistical analyses of data used were not performed. However, a computation of the best estimates of the Galactic rotation constants is not only an astronomical but also a metrological task. Here we perform an analysis of 53 R0 measurements (published in the past 20 years) to assess the consistency of the data. Our analysis shows that they are internally consistent. It is also shown that any trend in the R0 estimates from the last 20 years is statistically negligible, which renders the presence of a bandwagon effect doubtful. On the other hand, the formal errors in the published R0 estimates improve significantly with time.
Vleeshouwers, Jolien; Knardahl, Stein; Christensen, Jan Olav
2016-01-01
Study Objectives: This prospective cohort study examined previously underexplored relations between psychological/social work factors and troubled sleep in order to provide practical information about specific, modifiable factors at work. Methods: A comprehensive evaluation of a range of psychological/social work factors was obtained by several designs; i.e., cross-sectional analyses at baseline and follow-up, prospective analyses with baseline predictors (T1), prospective analyses with average exposure across waves as predictor ([T1 + T2] / 2), and prospective analyses with change in exposure from baseline to follow-up as predictor. Participants consisted of a sample of Norwegian employees from a broad spectrum of occupations, who completed a questionnaire at two points in time, approximately two years apart. Cross-sectional analyses at T1 comprised 7,459 participants, cross-sectional analyses at T2 included 6,688 participants. Prospective analyses comprised a sample 5,070 of participants who responded at both T1 and T2. Univariable and multivariable ordinal logistic regressions were performed. Results: Thirteen psychological/social work factors and two aspects of troubled sleep, namely difficulties initiating sleep and disturbed sleep, were studied. Ordinal logistic regressions revealed statistically significant associations for all psychological and social work factors in at least one of the analyses. Psychological and social work factors predicted sleep problems in the short term as well as the long term. Conclusions: All work factors investigated showed statistically significant associations with both sleep items, however quantitative job demands, decision control, role conflict, and support from superior were the most robust predictors and may therefore be suitable targets of interventions aimed at improving employee sleep. Citation: Vleeshouwers J, Knardahl S, Christensen JO. Effects of psychological and social work factors on self-reported sleep disturbance and difficulties initiating sleep. SLEEP 2016;39(4):833–846. PMID:26446114
Hutton, Brian; Wolfe, Dianna; Moher, David; Shamseer, Larissa
2017-05-01
Research waste has received considerable attention from the biomedical community. One noteworthy contributor is incomplete reporting in research publications. When detailing statistical methods and results, ensuring analytic methods and findings are completely documented improves transparency. For publications describing randomised trials and systematic reviews, guidelines have been developed to facilitate complete reporting. This overview summarises aspects of statistical reporting in trials and systematic reviews of health interventions. A narrative approach to summarise features regarding statistical methods and findings from reporting guidelines for trials and reviews was taken. We aim to enhance familiarity of statistical details that should be reported in biomedical research among statisticians and their collaborators. We summarise statistical reporting considerations for trials and systematic reviews from guidance documents including the Consolidated Standards of Reporting Trials (CONSORT) Statement for reporting of trials, the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) Statement for trial protocols, the Statistical Analyses and Methods in the Published Literature (SAMPL) Guidelines for statistical reporting principles, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Statement for systematic reviews and PRISMA for Protocols (PRISMA-P). Considerations regarding sharing of study data and statistical code are also addressed. Reporting guidelines provide researchers with minimum criteria for reporting. If followed, they can enhance research transparency and contribute improve quality of biomedical publications. Authors should employ these tools for planning and reporting of their research. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
ERIC Educational Resources Information Center
Thompson, Bruce; Melancon, Janet G.
Effect sizes have been increasingly emphasized in research as more researchers have recognized that: (1) all parametric analyses (t-tests, analyses of variance, etc.) are correlational; (2) effect sizes have played an important role in meta-analytic work; and (3) statistical significance testing is limited in its capacity to inform scientific…
Comments on `A Cautionary Note on the Interpretation of EOFs'.
NASA Astrophysics Data System (ADS)
Behera, Swadhin K.; Rao, Suryachandra A.; Saji, Hameed N.; Yamagata, Toshio
2003-04-01
The misleading aspect of the statistical analyses used in Dommenget and Latif, which raises concerns on some of the reported climate modes, is demonstrated. Adopting simple statistical techniques, the physical existence of the Indian Ocean dipole mode is shown and then the limitations of varimax and regression analyses in capturing the climate mode are discussed.
The heterogeneity statistic I(2) can be biased in small meta-analyses.
von Hippel, Paul T
2015-04-14
Estimated effects vary across studies, partly because of random sampling error and partly because of heterogeneity. In meta-analysis, the fraction of variance that is due to heterogeneity is estimated by the statistic I(2). We calculate the bias of I(2), focusing on the situation where the number of studies in the meta-analysis is small. Small meta-analyses are common; in the Cochrane Library, the median number of studies per meta-analysis is 7 or fewer. We use Mathematica software to calculate the expectation and bias of I(2). I(2) has a substantial bias when the number of studies is small. The bias is positive when the true fraction of heterogeneity is small, but the bias is typically negative when the true fraction of heterogeneity is large. For example, with 7 studies and no true heterogeneity, I(2) will overestimate heterogeneity by an average of 12 percentage points, but with 7 studies and 80 percent true heterogeneity, I(2) can underestimate heterogeneity by an average of 28 percentage points. Biases of 12-28 percentage points are not trivial when one considers that, in the Cochrane Library, the median I(2) estimate is 21 percent. The point estimate I(2) should be interpreted cautiously when a meta-analysis has few studies. In small meta-analyses, confidence intervals should supplement or replace the biased point estimate I(2).
NASA Astrophysics Data System (ADS)
Barette, Florian; Poppe, Sam; Smets, Benoît; Benbakkar, Mhammed; Kervyn, Matthieu
2017-10-01
We present an integrated, spatially-explicit database of existing geochemical major-element analyses available from (post-) colonial scientific reports, PhD Theses and international publications for the Virunga Volcanic Province, located in the western branch of the East African Rift System. This volcanic province is characterised by alkaline volcanism, including silica-undersaturated, alkaline and potassic lavas. The database contains a total of 908 geochemical analyses of eruptive rocks for the entire volcanic province with a localisation for most samples. A preliminary analysis of the overall consistency of the database, using statistical techniques on sets of geochemical analyses with contrasted analytical methods or dates, demonstrates that the database is consistent. We applied a principal component analysis and cluster analysis on whole-rock major element compositions included in the database to study the spatial variation of the chemical composition of eruptive products in the Virunga Volcanic Province. These statistical analyses identify spatially distributed clusters of eruptive products. The known geochemical contrasts are highlighted by the spatial analysis, such as the unique geochemical signature of Nyiragongo lavas compared to other Virunga lavas, the geochemical heterogeneity of the Bulengo area, and the trachyte flows of Karisimbi volcano. Most importantly, we identified separate clusters of eruptive products which originate from primitive magmatic sources. These lavas of primitive composition are preferentially located along NE-SW inherited rift structures, often at distance from the central Virunga volcanoes. Our results illustrate the relevance of a spatial analysis on integrated geochemical data for a volcanic province, as a complement to classical petrological investigations. This approach indeed helps to characterise geochemical variations within a complex of magmatic systems and to identify specific petrologic and geochemical investigations that should be tackled within a study area.
Metz, Anneke M
2008-01-01
There is an increasing need for students in the biological sciences to build a strong foundation in quantitative approaches to data analyses. Although most science, engineering, and math field majors are required to take at least one statistics course, statistical analysis is poorly integrated into undergraduate biology course work, particularly at the lower-division level. Elements of statistics were incorporated into an introductory biology course, including a review of statistics concepts and opportunity for students to perform statistical analysis in a biological context. Learning gains were measured with an 11-item statistics learning survey instrument developed for the course. Students showed a statistically significant 25% (p < 0.005) increase in statistics knowledge after completing introductory biology. Students improved their scores on the survey after completing introductory biology, even if they had previously completed an introductory statistics course (9%, improvement p < 0.005). Students retested 1 yr after completing introductory biology showed no loss of their statistics knowledge as measured by this instrument, suggesting that the use of statistics in biology course work may aid long-term retention of statistics knowledge. No statistically significant differences in learning were detected between male and female students in the study.
Khan, Asaduzzaman; Chien, Chi-Wen; Bagraith, Karl S
2015-04-01
To investigate whether using a parametric statistic in comparing groups leads to different conclusions when using summative scores from rating scales compared with using their corresponding Rasch-based measures. A Monte Carlo simulation study was designed to examine between-group differences in the change scores derived from summative scores from rating scales, and those derived from their corresponding Rasch-based measures, using 1-way analysis of variance. The degree of inconsistency between the 2 scoring approaches (i.e. summative and Rasch-based) was examined, using varying sample sizes, scale difficulties and person ability conditions. This simulation study revealed scaling artefacts that could arise from using summative scores rather than Rasch-based measures for determining the changes between groups. The group differences in the change scores were statistically significant for summative scores under all test conditions and sample size scenarios. However, none of the group differences in the change scores were significant when using the corresponding Rasch-based measures. This study raises questions about the validity of the inference on group differences of summative score changes in parametric analyses. Moreover, it provides a rationale for the use of Rasch-based measures, which can allow valid parametric analyses of rating scale data.
Jackson, Dan; Bowden, Jack
2016-09-07
Confidence intervals for the between study variance are useful in random-effects meta-analyses because they quantify the uncertainty in the corresponding point estimates. Methods for calculating these confidence intervals have been developed that are based on inverting hypothesis tests using generalised heterogeneity statistics. Whilst, under the random effects model, these new methods furnish confidence intervals with the correct coverage, the resulting intervals are usually very wide, making them uninformative. We discuss a simple strategy for obtaining 95 % confidence intervals for the between-study variance with a markedly reduced width, whilst retaining the nominal coverage probability. Specifically, we consider the possibility of using methods based on generalised heterogeneity statistics with unequal tail probabilities, where the tail probability used to compute the upper bound is greater than 2.5 %. This idea is assessed using four real examples and a variety of simulation studies. Supporting analytical results are also obtained. Our results provide evidence that using unequal tail probabilities can result in shorter 95 % confidence intervals for the between-study variance. We also show some further results for a real example that illustrates how shorter confidence intervals for the between-study variance can be useful when performing sensitivity analyses for the average effect, which is usually the parameter of primary interest. We conclude that using unequal tail probabilities when computing 95 % confidence intervals for the between-study variance, when using methods based on generalised heterogeneity statistics, can result in shorter confidence intervals. We suggest that those who find the case for using unequal tail probabilities convincing should use the '1-4 % split', where greater tail probability is allocated to the upper confidence bound. The 'width-optimal' interval that we present deserves further investigation.
Golder, Su; Loke, Yoon K.; Bland, Martin
2011-01-01
Background There is considerable debate as to the relative merits of using randomised controlled trial (RCT) data as opposed to observational data in systematic reviews of adverse effects. This meta-analysis of meta-analyses aimed to assess the level of agreement or disagreement in the estimates of harm derived from meta-analysis of RCTs as compared to meta-analysis of observational studies. Methods and Findings Searches were carried out in ten databases in addition to reference checking, contacting experts, citation searches, and hand-searching key journals, conference proceedings, and Web sites. Studies were included where a pooled relative measure of an adverse effect (odds ratio or risk ratio) from RCTs could be directly compared, using the ratio of odds ratios, with the pooled estimate for the same adverse effect arising from observational studies. Nineteen studies, yielding 58 meta-analyses, were identified for inclusion. The pooled ratio of odds ratios of RCTs compared to observational studies was estimated to be 1.03 (95% confidence interval 0.93–1.15). There was less discrepancy with larger studies. The symmetric funnel plot suggests that there is no consistent difference between risk estimates from meta-analysis of RCT data and those from meta-analysis of observational studies. In almost all instances, the estimates of harm from meta-analyses of the different study designs had 95% confidence intervals that overlapped (54/58, 93%). In terms of statistical significance, in nearly two-thirds (37/58, 64%), the results agreed (both studies showing a significant increase or significant decrease or both showing no significant difference). In only one meta-analysis about one adverse effect was there opposing statistical significance. Conclusions Empirical evidence from this overview indicates that there is no difference on average in the risk estimate of adverse effects of an intervention derived from meta-analyses of RCTs and meta-analyses of observational studies. This suggests that systematic reviews of adverse effects should not be restricted to specific study types. Please see later in the article for the Editors' Summary PMID:21559325
Mediation Analysis with Survival Outcomes: Accelerated Failure Time vs. Proportional Hazards Models.
Gelfand, Lois A; MacKinnon, David P; DeRubeis, Robert J; Baraldi, Amanda N
2016-01-01
Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and contain unobserved (censored) events. We present considerations for choosing an approach, using a comparison of semi-parametric proportional hazards (PH) and fully parametric accelerated failure time (AFT) approaches for illustration. We compare PH and AFT models and procedures in their integration into mediation models and review their ability to produce coefficients that estimate causal effects. Using simulation studies modeling Weibull-distributed survival times, we compare statistical properties of mediation analyses incorporating PH and AFT approaches (employing SAS procedures PHREG and LIFEREG, respectively) under varied data conditions, some including censoring. A simulated data set illustrates the findings. AFT models integrate more easily than PH models into mediation models. Furthermore, mediation analyses incorporating LIFEREG produce coefficients that can estimate causal effects, and demonstrate superior statistical properties. Censoring introduces bias in the coefficient estimate representing the treatment effect on outcome-underestimation in LIFEREG, and overestimation in PHREG. With LIFEREG, this bias can be addressed using an alternative estimate obtained from combining other coefficients, whereas this is not possible with PHREG. When Weibull assumptions are not violated, there are compelling advantages to using LIFEREG over PHREG for mediation analyses involving survival-time outcomes. Irrespective of the procedures used, the interpretation of coefficients, effects of censoring on coefficient estimates, and statistical properties should be taken into account when reporting results.
Gómez, Miguel A; Lorenzo, Alberto; Barakat, Rubén; Ortega, Enrique; Palao, José M
2008-02-01
The aim of the present study was to identify game-related statistics that differentiate winning and losing teams according to game location. The sample included 306 games of the 2004-2005 regular season of the Spanish professional men's league (ACB League). The independent variables were game location (home or away) and game result (win or loss). The game-related statistics registered were free throws (successful and unsuccessful), 2- and 3-point field goals (successful and unsuccessful), offensive and defensive rebounds, blocks, assists, fouls, steals, and turnovers. Descriptive and inferential analyses were done (one-way analysis of variance and discriminate analysis). The multivariate analysis showed that winning teams differ from losing teams in defensive rebounds (SC = .42) and in assists (SC = .38). Similarly, winning teams differ from losing teams when they play at home in defensive rebounds (SC = .40) and in assists (SC = .41). On the other hand, winning teams differ from losing teams when they play away in defensive rebounds (SC = .44), assists (SC = .30), successful 2-point field goals (SC = .31), and unsuccessful 3-point field goals (SC = -.35). Defensive rebounds and assists were the only game-related statistics common to all three analyses.
Using venlafaxine to treat behavioral disorders in patients with autism spectrum disorder.
Carminati, Giuliana Galli; Gerber, Fabienne; Darbellay, Barbara; Kosel, Markus Mathaus; Deriaz, Nicolas; Chabert, Jocelyne; Fathi, Marc; Bertschy, Gilles; Ferrero, François; Carminati, Federico
2016-02-04
To test the efficacy of venlafaxine at a dose of 18.75 mg/day on the reduction of behavioral problems such as irritability and hyperactivity/noncompliance in patients with intellectual disabilities and autism spectrum disorder (ASD). Our secondary hypothesis was that the usual doses of zuclopenthixol and/or clonazepam would decrease in the venlafaxine-treated group. In a randomized double-blind study, we compared six patients who received venlafaxine along with their usual treatment (zuclopenthixol and/or clonazepam) with seven patients who received placebo plus usual care. Irritability, hyperactivity/noncompliance, and overall clinical improvement were measured after 2 and 8 weeks, using validated clinical scales. Univariate analyses showed that the symptom of irritability improved in the entire sample (p = 0.023 after 2 weeks, p = 0.061 at study endpoint), although no difference was observed between the venlafaxine and placebo groups. No significant decrease in hyperactivity/noncompliance was observed during the study. At the end of the study, global improvement was observed in 33% of participants treated with venlafaxine and in 71% of participants in the placebo group (p = 0.29). The study found that decreased cumulative doses of clonazepam and zuclopenthixol were required for the venlafaxine group. Multivariate analyses (principal component analyses) with at least three combinations of variables showed that the two populations could be clearly separated (p b 0.05). Moreover, in all cases, the venlafaxine population had lower values for the Aberrant Behavior Checklist (ABC), Behavior Problems Inventory (BPI), and levels of urea with respect to the placebo group. In one case, a reduction in the dosage of clonazepam was also suggested. For an additional set of variables (ABC factor 2, BPI frequency of aggressive behaviors, hematic ammonia at Day 28, and zuclopenthixol and clonazepam intake), the separation between the two samples was statistically significant as was the Bartlett's test, but the Kaiser–Meyer–Olkin Measure of Sampling Adequacy was below the accepted threshold. This set of variables showed a reduction in the cumulative intake of both zuclopenthixol and clonazepam. Despite the small sample sizes, this study documented a statistically significant effect of venlafaxine. Moreover, we showed that lower doses of zuclopenthixol and clonazepam were needed in the venlafaxine group, although this difference was not statistically significant. This was confirmed by multivariate analyses, where this difference reached statistical significance when using a combination of variables involving zuclopenthixol. Larger-scale studies are recommended to better investigate the effectiveness of venlafaxine treatment in patients with intellectual disabilities and ASD.
Franke, Molly F; Jerome, J Gregory; Matias, Wilfredo R; Ternier, Ralph; Hilaire, Isabelle J; Harris, Jason B; Ivers, Louise C
2017-10-13
Case-control studies to quantify oral cholera vaccine effectiveness (VE) often rely on neighbors without diarrhea as community controls. Test-negative controls can be easily recruited and may minimize bias due to differential health-seeking behavior and recall. We compared VE estimates derived from community and test-negative controls and conducted bias-indicator analyses to assess potential bias with community controls. From October 2012 through November 2016, patients with acute watery diarrhea were recruited from cholera treatment centers in rural Haiti. Cholera cases had a positive stool culture. Non-cholera diarrhea cases (test-negative controls and non-cholera diarrhea cases for bias-indicator analyses) had a negative culture and rapid test. Up to four community controls were matched to diarrhea cases by age group, time, and neighborhood. Primary analyses included 181 cholera cases, 157 non-cholera diarrhea cases, 716 VE community controls and 625 bias-indicator community controls. VE for self-reported vaccination with two doses was consistent across the two control groups, with statistically significant VE estimates ranging from 72 to 74%. Sensitivity analyses revealed similar, though somewhat attenuated estimates for self-reported two dose VE. Bias-indicator estimates were consistently less than one, with VE estimates ranging from 19 to 43%, some of which were statistically significant. OCV estimates from case-control analyses using community and test-negative controls were similar. While bias-indicator analyses suggested possible over-estimation of VE estimates using community controls, test-negative analyses suggested this bias, if present, was minimal. Test-negative controls can be a valid low-cost and time-efficient alternative to community controls for OCV effectiveness estimation and may be especially relevant in emergency situations. Copyright © 2017. Published by Elsevier Ltd.
The impact of obesity surgery on musculoskeletal disease.
El-Khani, Ussamah; Ahmed, Ahmed; Hakky, Sherif; Nehme, Jean; Cousins, Jonathan; Chahal, Harvinder; Purkayastha, Sanjay
2014-12-01
Obesity is an important modifiable risk factor for musculoskeletal disease. A Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-compliant systematic review of bariatric surgery on musculoskeletal disease symptoms was performed. One thousand nineteen papers were identified, of which 43 were eligible for data synthesis. There were 79 results across 24 studies pertaining to physical capacity, of which 53 (67 %) demonstrated statistically significant post-operative improvement. There were 75 results across 33 studies pertaining to musculoskeletal pain, of which 42 (56 %) demonstrated a statistically significant post-operative improvement. There were 13 results across 6 studies pertaining to arthritis, of which 5 (38 %) demonstrated a statistically significant post-operative improvement. Bariatric surgery significantly improved musculoskeletal disease symptoms in 39 of the 43 studies. These changes were evident in a follow-up of 1 month to 10 years.
Campos-Filho, N; Franco, E L
1989-02-01
A frequent procedure in matched case-control studies is to report results from the multivariate unmatched analyses if they do not differ substantially from the ones obtained after conditioning on the matching variables. Although conceptually simple, this rule requires that an extensive series of logistic regression models be evaluated by both the conditional and unconditional maximum likelihood methods. Most computer programs for logistic regression employ only one maximum likelihood method, which requires that the analyses be performed in separate steps. This paper describes a Pascal microcomputer (IBM PC) program that performs multiple logistic regression by both maximum likelihood estimation methods, which obviates the need for switching between programs to obtain relative risk estimates from both matched and unmatched analyses. The program calculates most standard statistics and allows factoring of categorical or continuous variables by two distinct methods of contrast. A built-in, descriptive statistics option allows the user to inspect the distribution of cases and controls across categories of any given variable.
NASA Technical Reports Server (NTRS)
Chapanis, A.; Ochsman, R. B.; Parrish, R. N.; Weeks, G. D.
1972-01-01
Two-man teams solved credible, 'real-world' problems for which computer assistance has been or could be useful. Conversations were carried on in one of four modes of communication: (1) typewriting, (2) handwriting, (3) voice, and (4) natural, unrestricted communication. Two groups of subjects (experienced and inexperienced typists) were tested in the typewriting mode. Performance was assessed on three classes of dependent measures: time to solution, behavioral measures of activity, and linguistic measures. Significant and meaningful differences among the communication modes were found in each of the three classes of dependent variable. This paper is concerned mainly with the results of the activity analyses. Behavior was recorded in 15 different categories. The analyses of variance yielded 34 statistically significant terms of which 27 were judged to be practically significant as well. When the data were transformed to eliminate heterogeneity, the analyses of variance yielded 35 statistically significant terms of which 26 were judged to be practically significant.
Ceballos-Laita, Laura; Gutierrez-Carbonell, Elain; Takahashi, Daisuke; Abadía, Anunciación; Uemura, Matsuo; Abadía, Javier; López-Millán, Ana Flor
2018-04-01
This article contains consolidated proteomic data obtained from xylem sap collected from tomato plants grown in Fe- and Mn-sufficient control, as well as Fe-deficient and Mn-deficient conditions. Data presented here cover proteins identified and quantified by shotgun proteomics and Progenesis LC-MS analyses: proteins identified with at least two peptides and showing changes statistically significant (ANOVA; p ≤ 0.05) and above a biologically relevant selected threshold (fold ≥ 2) between treatments are listed. The comparison between Fe-deficient, Mn-deficient and control xylem sap samples using a multivariate statistical data analysis (Principal Component Analysis, PCA) is also included. Data included in this article are discussed in depth in the research article entitled "Effects of Fe and Mn deficiencies on the protein profiles of tomato ( Solanum lycopersicum) xylem sap as revealed by shotgun analyses" [1]. This dataset is made available to support the cited study as well to extend analyses at a later stage.
ERIC Educational Resources Information Center
Mulford, Bill; Silins, Halia
2011-01-01
Purpose: This study aims to present revised models and a reconceptualisation of successful school principalship for improved student outcomes. Design/methodology/approach: The study's approach is qualitative and quantitative, culminating in model building and multi-level statistical analyses. Findings: Principals who promote both capacity building…
Internet Use and Psychological Wellbeing: A Study of International Students in Singapore
ERIC Educational Resources Information Center
Dutta, Oindrila; Chye, Stefanie Yen Leng
2017-01-01
We investigated the relationship between psychological wellbeing (as indicated by participants' level of loneliness, perceived academic stress and depression) and generalized problematic internet use. Data was collected from a sample of 103 international students studying in Singapore. Statistical analyses revealed that depression was the most…
An Experimental Ecological Study of a Garden Compost Heap.
ERIC Educational Resources Information Center
Curds, Tracy
1985-01-01
A quantitative study of the fauna of a garden compost heap shows it to be similar to that of organisms found in soil and leaf litter. Materials, methods, and results are discussed and extensive tables of fauna lists, wet/dry masses, and statistical analyses are presented. (Author/DH)
Active control of aerothermoelastic effects for a conceptual hypersonic aircraft
NASA Technical Reports Server (NTRS)
Heeg, Jennifer; Gilbert, Michael G.; Pototzky, Anthony S.
1990-01-01
This paper describes the procedures for an results of aeroservothermoelastic studies. The objectives of these studies were to develop the necessary procedures for performing an aeroelastic analysis of an aerodynamically heated vehicle and to analyze a configuration in the classical 'cold' state and in a 'hot' state. Major tasks include the development of the structural and aerodynamic models, open loop analyses, design of active control laws for improving dynamic responses and analyses of the closed loop vehicles. The analyses performed focused on flutter speed calculations, short period eigenvalue trends and statistical analyses of the vehicle response to controls and turbulence. Improving the ride quality of the vehicle and raising the flutter boundary of the aerodynamically-heated vehicle up to that of the cold vehicle were the objectives of the control law design investigations.
Cohen, Jérémie F; Korevaar, Daniël A; Wang, Junfeng; Leeflang, Mariska M; Bossuyt, Patrick M
2016-09-01
To evaluate changes over time in summary estimates from meta-analyses of diagnostic accuracy studies. We included 48 meta-analyses from 35 MEDLINE-indexed systematic reviews published between September 2011 and January 2012 (743 diagnostic accuracy studies; 344,015 participants). Within each meta-analysis, we ranked studies by publication date. We applied random-effects cumulative meta-analysis to follow how summary estimates of sensitivity and specificity evolved over time. Time trends were assessed by fitting a weighted linear regression model of the summary accuracy estimate against rank of publication. The median of the 48 slopes was -0.02 (-0.08 to 0.03) for sensitivity and -0.01 (-0.03 to 0.03) for specificity. Twelve of 96 (12.5%) time trends in sensitivity or specificity were statistically significant. We found a significant time trend in at least one accuracy measure for 11 of the 48 (23%) meta-analyses. Time trends in summary estimates are relatively frequent in meta-analyses of diagnostic accuracy studies. Results from early meta-analyses of diagnostic accuracy studies should be considered with caution. Copyright © 2016 Elsevier Inc. All rights reserved.
Personal use of hair dyes and the risk of bladder cancer: results of a meta-analysis.
Huncharek, Michael; Kupelnick, Bruce
2005-01-01
OBJECTIVE: This study examined the methodology of observational studies that explored an association between personal use of hair dye products and the risk of bladder cancer. METHODS: Data were pooled from epidemiological studies using a general variance-based meta-analytic method that employed confidence intervals. The outcome of interest was a summary relative risk (RRs) reflecting the risk of bladder cancer development associated with use of hair dye products vs. non-use. Sensitivity analyses were performed to explain any observed statistical heterogeneity and to explore the influence of specific study characteristics of the summary estimate of effect. RESULTS: Initially combining homogenous data from six case-control and one cohort study yielded a non-significant RR of 1.01 (0.92, 1.11), suggesting no association between hair dye use and bladder cancer development. Sensitivity analyses examining the influence of hair dye type, color, and study design on this suspected association showed that uncontrolled confounding and design limitations contributed to a spurious non-significant summary RR. The sensitivity analyses yielded statistically significant RRs ranging from 1.22 (1.11, 1.51) to 1.50 (1.30, 1.98), indicating that personal use of hair dye products increases bladder cancer risk by 22% to 50% vs. non-use. CONCLUSION: The available epidemiological data suggest an association between personal use of hair dye products and increased risk of bladder cancer. PMID:15736329
Living systematic reviews: 3. Statistical methods for updating meta-analyses.
Simmonds, Mark; Salanti, Georgia; McKenzie, Joanne; Elliott, Julian
2017-11-01
A living systematic review (LSR) should keep the review current as new research evidence emerges. Any meta-analyses included in the review will also need updating as new material is identified. If the aim of the review is solely to present the best current evidence standard meta-analysis may be sufficient, provided reviewers are aware that results may change at later updates. If the review is used in a decision-making context, more caution may be needed. When using standard meta-analysis methods, the chance of incorrectly concluding that any updated meta-analysis is statistically significant when there is no effect (the type I error) increases rapidly as more updates are performed. Inaccurate estimation of any heterogeneity across studies may also lead to inappropriate conclusions. This paper considers four methods to avoid some of these statistical problems when updating meta-analyses: two methods, that is, law of the iterated logarithm and the Shuster method control primarily for inflation of type I error and two other methods, that is, trial sequential analysis and sequential meta-analysis control for type I and II errors (failing to detect a genuine effect) and take account of heterogeneity. This paper compares the methods and considers how they could be applied to LSRs. Copyright © 2017 Elsevier Inc. All rights reserved.
2011-01-01
Braunholtz D et al. The proportion of upper gastrointestinal symptoms in the community associated with Helicobacter pylori , lifestyle factors, and...controls. Statistical analyses were performed using SAS vs. 8.2 for Win- dows (SAS Institute, Cary , NC). Two- tailed statistical significance was...however a study looking at perceived need . for dental care among recruits found that Navy recruits were less likely to perceive a need for dental
ERIC Educational Resources Information Center
Lee, Jennifer
2012-01-01
The intent of this study was to examine the relationship between media multitasking orientation and grade point average. The study utilized a mixed-methods approach to investigate the research questions. In the quantitative section of the study, the primary method of statistical analyses was multiple regression. The independent variables for the…
Makarewicz, Roman; Kopczyńska, Ewa; Marszałek, Andrzej; Goralewska, Alina; Kardymowicz, Hanna
2012-01-01
Aim of the study This retrospective study attempts to evaluate the influence of serum vascular endothelial growth factor C (VEGF-C), microvessel density (MVD) and lymphatic vessel density (LMVD) on the result of tumour treatment in women with cervical cancer. Material and methods The research was carried out in a group of 58 patients scheduled for brachytherapy for cervical cancer. All women were patients of the Department and University Hospital of Oncology and Brachytherapy, Collegium Medicum in Bydgoszcz of Nicolaus Copernicus University in Toruń. VEGF-C was determined by means of a quantitative sandwich enzyme immunoassay using a human antibody VEGF-C ELISA produced by Bender MedSystem, enzyme-linked immunosorbent detecting the activity of human VEGF-C in body fluids. The measure for the intensity of angiogenesis and lymphangiogenesis in immunohistochemical reactions is the number of blood vessels within the tumour. Statistical analysis was done using Statistica 6.0 software (StatSoft, Inc. 2001). The Cox proportional hazards model was used for univariate and multivariate analyses. Univariate analysis of overall survival was performed as outlined by Kaplan and Meier. In all statistical analyses p < 0.05 (marked red) was taken as significant. Results In 51 patients who showed up for follow-up examination, the influence of the factors of angiogenesis, lymphangiogenesis, patients’ age and the level of haemoglobin at the end of treatment were assessed. Selected variables, such as patients’ age, lymph vessel density (LMVD), microvessel density (MVD) and the level of haemoglobin (Hb) before treatment were analysed by means of Cox logical regression as potential prognostic factors for lymph node invasion. The observed differences were statistically significant for haemoglobin level before treatment and the platelet number after treatment. The study revealed the following prognostic factors: lymph node status, FIGO stage, and kind of treatment. No statistically significant influence of angiogenic and lymphangiogenic factors on the prognosis was found. Conclusion Angiogenic and lymphangiogenic factors have no value in predicting response to radiotherapy in cervical cancer patients. PMID:23788848
Racial disparities in diabetes mortality in the 50 most populous US cities.
Rosenstock, Summer; Whitman, Steve; West, Joseph F; Balkin, Michael
2014-10-01
While studies have consistently shown that in the USA, non-Hispanic Blacks (Blacks) have higher diabetes prevalence, complication and death rates than non-Hispanic Whites (Whites), there are no studies that compare disparities in diabetes mortality across the largest US cities. This study presents and compares Black/White age-adjusted diabetes mortality rate ratios (RRs), calculated using national death files and census data, for the 50 most populous US cities. Relationships between city-level diabetes mortality RRs and 12 ecological variables were explored using bivariate correlation analyses. Multivariate analyses were conducted using negative binomial regression to examine how much of the disparity could be explained by these variables. Blacks had statistically significantly higher mortality rates compared to Whites in 39 of the 41 cities included in analyses, with statistically significant rate ratios ranging from 1.57 (95 % CI: 1.33-1.86) in Baltimore to 3.78 (95 % CI: 2.84-5.02) in Washington, DC. Analyses showed that economic inequality was strongly correlated with the diabetes mortality disparity, driven by differences in White poverty levels. This was followed by segregation. Multivariate analyses showed that adjusting for Black/White poverty alone explained 58.5 % of the disparity. Adjusting for Black/White poverty and segregation explained 72.6 % of the disparity. This study emphasizes the role that inequalities in social and economic determinants, rather than for example poverty on its own, play in Black/White diabetes mortality disparities. It also highlights how the magnitude of the disparity and the factors that influence it can vary greatly across cities, underscoring the importance of using local data to identify context specific barriers and develop effective interventions to eliminate health disparities.
DESIGNING ENVIRONMENTAL MONITORING DATABASES FOR STATISTIC ASSESSMENT
Databases designed for statistical analyses have characteristics that distinguish them from databases intended for general use. EMAP uses a probabilistic sampling design to collect data to produce statistical assessments of environmental conditions. In addition to supporting the ...
Nonnormality and Divergence in Posttreatment Alcohol Use
Witkiewitz, Katie; van der Maas, Han L. J.; Hufford, Michael R.; Marlatt, G. Alan
2007-01-01
Alcohol lapses are the modal outcome following treatment for alcohol use disorders, yet many alcohol researchers have encountered limited success in the prediction and prevention of relapse. One hypothesis is that lapses are unpredictable, but another possibility is the complexity of the relapse process is not captured by traditional statistical methods. Data from Project Matching Alcohol Treatments to Client Heterogeneity (Project MATCH), a multisite alcohol treatment study, were reanalyzed with 2 statistical methodologies: catastrophe and 2-part growth mixture modeling. Drawing on previous investigations of self-efficacy as a dynamic predictor of relapse, the current study revisits the self-efficacy matching hypothesis, which was not statistically supported in Project MATCH. Results from both the catastrophe and growth mixture analyses demonstrated a dynamic relationship between self-efficacy and drinking outcomes. The growth mixture analyses provided evidence in support of the original matching hypothesis: Individuals with lower self-efficacy who received cognitive behavior therapy drank far less frequently than did those with low self-efficacy who received motivational therapy. These results highlight the dynamical nature of the relapse process and the importance of the use of methodologies that accommodate this complexity when evaluating treatment outcomes. PMID:17516769
Study/Experimental/Research Design: Much More Than Statistics
Knight, Kenneth L.
2010-01-01
Abstract Context: The purpose of study, experimental, or research design in scientific manuscripts has changed significantly over the years. It has evolved from an explanation of the design of the experiment (ie, data gathering or acquisition) to an explanation of the statistical analysis. This practice makes “Methods” sections hard to read and understand. Objective: To clarify the difference between study design and statistical analysis, to show the advantages of a properly written study design on article comprehension, and to encourage authors to correctly describe study designs. Description: The role of study design is explored from the introduction of the concept by Fisher through modern-day scientists and the AMA Manual of Style. At one time, when experiments were simpler, the study design and statistical design were identical or very similar. With the complex research that is common today, which often includes manipulating variables to create new variables and the multiple (and different) analyses of a single data set, data collection is very different than statistical design. Thus, both a study design and a statistical design are necessary. Advantages: Scientific manuscripts will be much easier to read and comprehend. A proper experimental design serves as a road map to the study methods, helping readers to understand more clearly how the data were obtained and, therefore, assisting them in properly analyzing the results. PMID:20064054
2012-01-01
Background A statistical analysis plan (SAP) is a critical link between how a clinical trial is conducted and the clinical study report. To secure objective study results, regulatory bodies expect that the SAP will meet requirements in pre-specifying inferential analyses and other important statistical techniques. To write a good SAP for model-based sensitivity and ancillary analyses involves non-trivial decisions on and justification of many aspects of the chosen setting. In particular, trials with longitudinal count data as primary endpoints pose challenges for model choice and model validation. In the random effects setting, frequentist strategies for model assessment and model diagnosis are complex and not easily implemented and have several limitations. Therefore, it is of interest to explore Bayesian alternatives which provide the needed decision support to finalize a SAP. Methods We focus on generalized linear mixed models (GLMMs) for the analysis of longitudinal count data. A series of distributions with over- and under-dispersion is considered. Additionally, the structure of the variance components is modified. We perform a simulation study to investigate the discriminatory power of Bayesian tools for model criticism in different scenarios derived from the model setting. We apply the findings to the data from an open clinical trial on vertigo attacks. These data are seen as pilot data for an ongoing phase III trial. To fit GLMMs we use a novel Bayesian computational approach based on integrated nested Laplace approximations (INLAs). The INLA methodology enables the direct computation of leave-one-out predictive distributions. These distributions are crucial for Bayesian model assessment. We evaluate competing GLMMs for longitudinal count data according to the deviance information criterion (DIC) or probability integral transform (PIT), and by using proper scoring rules (e.g. the logarithmic score). Results The instruments under study provide excellent tools for preparing decisions within the SAP in a transparent way when structuring the primary analysis, sensitivity or ancillary analyses, and specific analyses for secondary endpoints. The mean logarithmic score and DIC discriminate well between different model scenarios. It becomes obvious that the naive choice of a conventional random effects Poisson model is often inappropriate for real-life count data. The findings are used to specify an appropriate mixed model employed in the sensitivity analyses of an ongoing phase III trial. Conclusions The proposed Bayesian methods are not only appealing for inference but notably provide a sophisticated insight into different aspects of model performance, such as forecast verification or calibration checks, and can be applied within the model selection process. The mean of the logarithmic score is a robust tool for model ranking and is not sensitive to sample size. Therefore, these Bayesian model selection techniques offer helpful decision support for shaping sensitivity and ancillary analyses in a statistical analysis plan of a clinical trial with longitudinal count data as the primary endpoint. PMID:22962944
Adrion, Christine; Mansmann, Ulrich
2012-09-10
A statistical analysis plan (SAP) is a critical link between how a clinical trial is conducted and the clinical study report. To secure objective study results, regulatory bodies expect that the SAP will meet requirements in pre-specifying inferential analyses and other important statistical techniques. To write a good SAP for model-based sensitivity and ancillary analyses involves non-trivial decisions on and justification of many aspects of the chosen setting. In particular, trials with longitudinal count data as primary endpoints pose challenges for model choice and model validation. In the random effects setting, frequentist strategies for model assessment and model diagnosis are complex and not easily implemented and have several limitations. Therefore, it is of interest to explore Bayesian alternatives which provide the needed decision support to finalize a SAP. We focus on generalized linear mixed models (GLMMs) for the analysis of longitudinal count data. A series of distributions with over- and under-dispersion is considered. Additionally, the structure of the variance components is modified. We perform a simulation study to investigate the discriminatory power of Bayesian tools for model criticism in different scenarios derived from the model setting. We apply the findings to the data from an open clinical trial on vertigo attacks. These data are seen as pilot data for an ongoing phase III trial. To fit GLMMs we use a novel Bayesian computational approach based on integrated nested Laplace approximations (INLAs). The INLA methodology enables the direct computation of leave-one-out predictive distributions. These distributions are crucial for Bayesian model assessment. We evaluate competing GLMMs for longitudinal count data according to the deviance information criterion (DIC) or probability integral transform (PIT), and by using proper scoring rules (e.g. the logarithmic score). The instruments under study provide excellent tools for preparing decisions within the SAP in a transparent way when structuring the primary analysis, sensitivity or ancillary analyses, and specific analyses for secondary endpoints. The mean logarithmic score and DIC discriminate well between different model scenarios. It becomes obvious that the naive choice of a conventional random effects Poisson model is often inappropriate for real-life count data. The findings are used to specify an appropriate mixed model employed in the sensitivity analyses of an ongoing phase III trial. The proposed Bayesian methods are not only appealing for inference but notably provide a sophisticated insight into different aspects of model performance, such as forecast verification or calibration checks, and can be applied within the model selection process. The mean of the logarithmic score is a robust tool for model ranking and is not sensitive to sample size. Therefore, these Bayesian model selection techniques offer helpful decision support for shaping sensitivity and ancillary analyses in a statistical analysis plan of a clinical trial with longitudinal count data as the primary endpoint.
NASA Astrophysics Data System (ADS)
Karuppiah, R.; Faldi, A.; Laurenzi, I.; Usadi, A.; Venkatesh, A.
2014-12-01
An increasing number of studies are focused on assessing the environmental footprint of different products and processes, especially using life cycle assessment (LCA). This work shows how combining statistical methods and Geographic Information Systems (GIS) with environmental analyses can help improve the quality of results and their interpretation. Most environmental assessments in literature yield single numbers that characterize the environmental impact of a process/product - typically global or country averages, often unchanging in time. In this work, we show how statistical analysis and GIS can help address these limitations. For example, we demonstrate a method to separately quantify uncertainty and variability in the result of LCA models using a power generation case study. This is important for rigorous comparisons between the impacts of different processes. Another challenge is lack of data that can affect the rigor of LCAs. We have developed an approach to estimate environmental impacts of incompletely characterized processes using predictive statistical models. This method is applied to estimate unreported coal power plant emissions in several world regions. There is also a general lack of spatio-temporal characterization of the results in environmental analyses. For instance, studies that focus on water usage do not put in context where and when water is withdrawn. Through the use of hydrological modeling combined with GIS, we quantify water stress on a regional and seasonal basis to understand water supply and demand risks for multiple users. Another example where it is important to consider regional dependency of impacts is when characterizing how agricultural land occupation affects biodiversity in a region. We developed a data-driven methodology used in conjuction with GIS to determine if there is a statistically significant difference between the impacts of growing different crops on different species in various biomes of the world.
Redmond, Tony; O'Leary, Neil; Hutchison, Donna M; Nicolela, Marcelo T; Artes, Paul H; Chauhan, Balwantray C
2013-12-01
A new analysis method called permutation of pointwise linear regression measures the significance of deterioration over time at each visual field location, combines the significance values into an overall statistic, and then determines the likelihood of change in the visual field. Because the outcome is a single P value, individualized to that specific visual field and independent of the scale of the original measurement, the method is well suited for comparing techniques with different stimuli and scales. To test the hypothesis that frequency-doubling matrix perimetry (FDT2) is more sensitive than standard automated perimetry (SAP) in identifying visual field progression in glaucoma. Patients with open-angle glaucoma and healthy controls were examined by FDT2 and SAP, both with the 24-2 test pattern, on the same day at 6-month intervals in a longitudinal prospective study conducted in a hospital-based setting. Only participants with at least 5 examinations were included. Data were analyzed with permutation of pointwise linear regression. Permutation of pointwise linear regression is individualized to each participant, in contrast to current analyses in which the statistical significance is inferred from population-based approaches. Analyses were performed with both total deviation and pattern deviation. Sixty-four patients and 36 controls were included in the study. The median age, SAP mean deviation, and follow-up period were 65 years, -2.6 dB, and 5.4 years, respectively, in patients and 62 years, +0.4 dB, and 5.2 years, respectively, in controls. Using total deviation analyses, statistically significant deterioration was identified in 17% of patients with FDT2, in 34% of patients with SAP, and in 14% of patients with both techniques; in controls these percentages were 8% with FDT2, 31% with SAP, and 8% with both. Using pattern deviation analyses, statistically significant deterioration was identified in 16% of patients with FDT2, in 17% of patients with SAP, and in 3% of patients with both techniques; in controls these values were 3% with FDT2 and none with SAP. No evidence was found that FDT2 is more sensitive than SAP in identifying visual field deterioration. In about one-third of healthy controls, age-related deterioration with SAP reached statistical significance.
USDA-ARS?s Scientific Manuscript database
Agronomic and Environmental research experiments result in data that are analyzed using statistical methods. These data are unavoidably accompanied by uncertainty. Decisions about hypotheses, based on statistical analyses of these data are therefore subject to error. This error is of three types,...
The Large-Scale Structure of Semantic Networks: Statistical Analyses and a Model of Semantic Growth
ERIC Educational Resources Information Center
Steyvers, Mark; Tenenbaum, Joshua B.
2005-01-01
We present statistical analyses of the large-scale structure of 3 types of semantic networks: word associations, WordNet, and Roget's Thesaurus. We show that they have a small-world structure, characterized by sparse connectivity, short average path lengths between words, and strong local clustering. In addition, the distributions of the number of…
Quadriceps Tendon Autograft in Anterior Cruciate Ligament Reconstruction: A Systematic Review.
Hurley, Eoghan T; Calvo-Gurry, Manuel; Withers, Dan; Farrington, Shane K; Moran, Ray; Moran, Cathal J
2018-05-01
To systematically review the current evidence to ascertain whether quadriceps tendon autograft (QT) is a viable option in anterior cruciate ligament reconstruction. A literature review was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. Cohort studies comparing QT with bone-patellar tendon-bone autograft (BPTB) or hamstring tendon autograft (HT) were included. Clinical outcomes were compared, with all statistical analyses performed using IBM SPSS Statistics for Windows, version 22.0, with P < .05 being considered statistically significant. We identified 15 clinical trials with 1,910 patients. In all included studies, QT resulted in lower rates of anterior knee pain than BPTB. There was no difference in the rate of graft rupture between QT and BPTB or HT in any of the studies reporting this. One study found that QT resulted in greater knee stability than BPTB, and another study found increased stability compared with HT. One study found that QT resulted in improved functional outcomes compared with BPTB, and another found improved outcomes compared with HT, but one study found worse outcomes compared with BPTB. Current literature suggests QT is a viable option in anterior cruciate ligament reconstruction, with published literature showing comparable knee stability, functional outcomes, donor-site morbidity, and rerupture rates compared with BPTB and HT. Level III, systematic review of Level I, II, and III studies. Copyright © 2018 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.
Cunningham, Michael R.; Baumeister, Roy F.
2016-01-01
The limited resource model states that self-control is governed by a relatively finite set of inner resources on which people draw when exerting willpower. Once self-control resources have been used up or depleted, they are less available for other self-control tasks, leading to a decrement in subsequent self-control success. The depletion effect has been studied for over 20 years, tested or extended in more than 600 studies, and supported in an independent meta-analysis (Hagger et al., 2010). Meta-analyses are supposed to reduce bias in literature reviews. Carter et al.’s (2015) meta-analysis, by contrast, included a series of questionable decisions involving sampling, methods, and data analysis. We provide quantitative analyses of key sampling issues: exclusion of many of the best depletion studies based on idiosyncratic criteria and the emphasis on mini meta-analyses with low statistical power as opposed to the overall depletion effect. We discuss two key methodological issues: failure to code for research quality, and the quantitative impact of weak studies by novice researchers. We discuss two key data analysis issues: questionable interpretation of the results of trim and fill and Funnel Plot Asymmetry test procedures, and the use and misinterpretation of the untested Precision Effect Test and Precision Effect Estimate with Standard Error (PEESE) procedures. Despite these serious problems, the Carter et al. (2015) meta-analysis results actually indicate that there is a real depletion effect – contrary to their title. PMID:27826272
Spedding, Simon
2014-01-01
Efficacy of Vitamin D supplements in depression is controversial, awaiting further literature analysis. Biological flaws in primary studies is a possible reason meta-analyses of Vitamin D have failed to demonstrate efficacy. This systematic review and meta-analysis of Vitamin D and depression compared studies with and without biological flaws. The systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The literature search was undertaken through four databases for randomized controlled trials (RCTs). Studies were critically appraised for methodological quality and biological flaws, in relation to the hypothesis and study design. Meta-analyses were performed for studies according to the presence of biological flaws. The 15 RCTs identified provide a more comprehensive evidence-base than previous systematic reviews; methodological quality of studies was generally good and methodology was diverse. A meta-analysis of all studies without flaws demonstrated a statistically significant improvement in depression with Vitamin D supplements (+0.78 CI +0.24, +1.27). Studies with biological flaws were mainly inconclusive, with the meta-analysis demonstrating a statistically significant worsening in depression by taking Vitamin D supplements (−1.1 CI −0.7, −1.5). Vitamin D supplementation (≥800 I.U. daily) was somewhat favorable in the management of depression in studies that demonstrate a change in vitamin levels, and the effect size was comparable to that of anti-depressant medication. PMID:24732019
msap: a tool for the statistical analysis of methylation-sensitive amplified polymorphism data.
Pérez-Figueroa, A
2013-05-01
In this study msap, an R package which analyses methylation-sensitive amplified polymorphism (MSAP or MS-AFLP) data is presented. The program provides a deep analysis of epigenetic variation starting from a binary data matrix indicating the banding pattern between the isoesquizomeric endonucleases HpaII and MspI, with differential sensitivity to cytosine methylation. After comparing the restriction fragments, the program determines if each fragment is susceptible to methylation (representative of epigenetic variation) or if there is no evidence of methylation (representative of genetic variation). The package provides, in a user-friendly command line interface, a pipeline of different analyses of the variation (genetic and epigenetic) among user-defined groups of samples, as well as the classification of the methylation occurrences in those groups. Statistical testing provides support to the analyses. A comprehensive report of the analyses and several useful plots could help researchers to assess the epigenetic and genetic variation in their MSAP experiments. msap is downloadable from CRAN (http://cran.r-project.org/) and its own webpage (http://msap.r-forge.R-project.org/). The package is intended to be easy to use even for those people unfamiliar with the R command line environment. Advanced users may take advantage of the available source code to adapt msap to more complex analyses. © 2013 Blackwell Publishing Ltd.
Multi-trait analysis of genome-wide association summary statistics using MTAG.
Turley, Patrick; Walters, Raymond K; Maghzian, Omeed; Okbay, Aysu; Lee, James J; Fontana, Mark Alan; Nguyen-Viet, Tuan Anh; Wedow, Robbee; Zacher, Meghan; Furlotte, Nicholas A; Magnusson, Patrik; Oskarsson, Sven; Johannesson, Magnus; Visscher, Peter M; Laibson, David; Cesarini, David; Neale, Benjamin M; Benjamin, Daniel J
2018-02-01
We introduce multi-trait analysis of GWAS (MTAG), a method for joint analysis of summary statistics from genome-wide association studies (GWAS) of different traits, possibly from overlapping samples. We apply MTAG to summary statistics for depressive symptoms (N eff = 354,862), neuroticism (N = 168,105), and subjective well-being (N = 388,538). As compared to the 32, 9, and 13 genome-wide significant loci identified in the single-trait GWAS (most of which are themselves novel), MTAG increases the number of associated loci to 64, 37, and 49, respectively. Moreover, association statistics from MTAG yield more informative bioinformatics analyses and increase the variance explained by polygenic scores by approximately 25%, matching theoretical expectations.
Practice-based evidence study design for comparative effectiveness research.
Horn, Susan D; Gassaway, Julie
2007-10-01
To describe a new, rigorous, comprehensive practice-based evidence for clinical practice improvement (PBE-CPI) study methodology, and compare its features, advantages, and disadvantages to those of randomized controlled trials and sophisticated statistical methods for comparative effectiveness research. PBE-CPI incorporates natural variation within data from routine clinical practice to determine what works, for whom, when, and at what cost. It uses the knowledge of front-line caregivers, who develop study questions and define variables as part of a transdisciplinary team. Its comprehensive measurement framework provides a basis for analyses of significant bivariate and multivariate associations between treatments and outcomes, controlling for patient differences, such as severity of illness. PBE-CPI studies can uncover better practices more quickly than randomized controlled trials or sophisticated statistical methods, while achieving many of the same advantages. We present examples of actionable findings from PBE-CPI studies in postacute care settings related to comparative effectiveness of medications, nutritional support approaches, incontinence products, physical therapy activities, and other services. Outcomes improved when practices associated with better outcomes in PBE-CPI analyses were adopted in practice.
Nour-Eldein, Hebatallah
2016-01-01
With limited statistical knowledge of most physicians it is not uncommon to find statistical errors in research articles. To determine the statistical methods and to assess the statistical errors in family medicine (FM) research articles that were published between 2010 and 2014. This was a cross-sectional study. All 66 FM research articles that were published over 5 years by FM authors with affiliation to Suez Canal University were screened by the researcher between May and August 2015. Types and frequencies of statistical methods were reviewed in all 66 FM articles. All 60 articles with identified inferential statistics were examined for statistical errors and deficiencies. A comprehensive 58-item checklist based on statistical guidelines was used to evaluate the statistical quality of FM articles. Inferential methods were recorded in 62/66 (93.9%) of FM articles. Advanced analyses were used in 29/66 (43.9%). Contingency tables 38/66 (57.6%), regression (logistic, linear) 26/66 (39.4%), and t-test 17/66 (25.8%) were the most commonly used inferential tests. Within 60 FM articles with identified inferential statistics, no prior sample size 19/60 (31.7%), application of wrong statistical tests 17/60 (28.3%), incomplete documentation of statistics 59/60 (98.3%), reporting P value without test statistics 32/60 (53.3%), no reporting confidence interval with effect size measures 12/60 (20.0%), use of mean (standard deviation) to describe ordinal/nonnormal data 8/60 (13.3%), and errors related to interpretation were mainly for conclusions without support by the study data 5/60 (8.3%). Inferential statistics were used in the majority of FM articles. Data analysis and reporting statistics are areas for improvement in FM research articles.
Nour-Eldein, Hebatallah
2016-01-01
Background: With limited statistical knowledge of most physicians it is not uncommon to find statistical errors in research articles. Objectives: To determine the statistical methods and to assess the statistical errors in family medicine (FM) research articles that were published between 2010 and 2014. Methods: This was a cross-sectional study. All 66 FM research articles that were published over 5 years by FM authors with affiliation to Suez Canal University were screened by the researcher between May and August 2015. Types and frequencies of statistical methods were reviewed in all 66 FM articles. All 60 articles with identified inferential statistics were examined for statistical errors and deficiencies. A comprehensive 58-item checklist based on statistical guidelines was used to evaluate the statistical quality of FM articles. Results: Inferential methods were recorded in 62/66 (93.9%) of FM articles. Advanced analyses were used in 29/66 (43.9%). Contingency tables 38/66 (57.6%), regression (logistic, linear) 26/66 (39.4%), and t-test 17/66 (25.8%) were the most commonly used inferential tests. Within 60 FM articles with identified inferential statistics, no prior sample size 19/60 (31.7%), application of wrong statistical tests 17/60 (28.3%), incomplete documentation of statistics 59/60 (98.3%), reporting P value without test statistics 32/60 (53.3%), no reporting confidence interval with effect size measures 12/60 (20.0%), use of mean (standard deviation) to describe ordinal/nonnormal data 8/60 (13.3%), and errors related to interpretation were mainly for conclusions without support by the study data 5/60 (8.3%). Conclusion: Inferential statistics were used in the majority of FM articles. Data analysis and reporting statistics are areas for improvement in FM research articles. PMID:27453839
Ng'andu, N H
1997-03-30
In the analysis of survival data using the Cox proportional hazard (PH) model, it is important to verify that the explanatory variables analysed satisfy the proportional hazard assumption of the model. This paper presents results of a simulation study that compares five test statistics to check the proportional hazard assumption of Cox's model. The test statistics were evaluated under proportional hazards and the following types of departures from the proportional hazard assumption: increasing relative hazards; decreasing relative hazards; crossing hazards; diverging hazards, and non-monotonic hazards. The test statistics compared include those based on partitioning of failure time and those that do not require partitioning of failure time. The simulation results demonstrate that the time-dependent covariate test, the weighted residuals score test and the linear correlation test have equally good power for detection of non-proportionality in the varieties of non-proportional hazards studied. Using illustrative data from the literature, these test statistics performed similarly.
Petersson, K M; Nichols, T E; Poline, J B; Holmes, A P
1999-01-01
Functional neuroimaging (FNI) provides experimental access to the intact living brain making it possible to study higher cognitive functions in humans. In this review and in a companion paper in this issue, we discuss some common methods used to analyse FNI data. The emphasis in both papers is on assumptions and limitations of the methods reviewed. There are several methods available to analyse FNI data indicating that none is optimal for all purposes. In order to make optimal use of the methods available it is important to know the limits of applicability. For the interpretation of FNI results it is also important to take into account the assumptions, approximations and inherent limitations of the methods used. This paper gives a brief overview over some non-inferential descriptive methods and common statistical models used in FNI. Issues relating to the complex problem of model selection are discussed. In general, proper model selection is a necessary prerequisite for the validity of the subsequent statistical inference. The non-inferential section describes methods that, combined with inspection of parameter estimates and other simple measures, can aid in the process of model selection and verification of assumptions. The section on statistical models covers approaches to global normalization and some aspects of univariate, multivariate, and Bayesian models. Finally, approaches to functional connectivity and effective connectivity are discussed. In the companion paper we review issues related to signal detection and statistical inference. PMID:10466149
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dong, Lihua; Cui, Jingkun; Tang, Fengjiao
Purpose: Studies of the association between ataxia telangiectasia–mutated (ATM) gene polymorphisms and acute radiation injuries are often small in sample size, and the results are inconsistent. We conducted the first meta-analysis to provide a systematic review of published findings. Methods and Materials: Publications were identified by searching PubMed up to April 25, 2014. Primary meta-analysis was performed for all acute radiation injuries, and subgroup meta-analyses were based on clinical endpoint. The influence of sample size and radiation injury incidence on genetic effects was estimated in sensitivity analyses. Power calculations were also conducted. Results: The meta-analysis was conducted on the ATMmore » polymorphism rs1801516, including 5 studies with 1588 participants. For all studies, the cut-off for differentiating cases from controls was grade 2 acute radiation injuries. The primary meta-analysis showed a significant association with overall acute radiation injuries (allelic model: odds ratio = 1.33, 95% confidence interval: 1.04-1.71). Subgroup analyses detected an association between the rs1801516 polymorphism and a significant increase in urinary and lower gastrointestinal injuries and an increase in skin injury that was not statistically significant. There was no between-study heterogeneity in any meta-analyses. In the sensitivity analyses, small studies did not show larger effects than large studies. In addition, studies with high incidence of acute radiation injuries showed larger effects than studies with low incidence. Power calculations revealed that the statistical power of the primary meta-analysis was borderline, whereas there was adequate power for the subgroup analysis of studies with high incidence of acute radiation injuries. Conclusions: Our meta-analysis showed a consistency of the results from the overall and subgroup analyses. We also showed that the genetic effect of the rs1801516 polymorphism on acute radiation injuries was dependent on the incidence of the injury. These support the evidence of an association between the rs1801516 polymorphism and acute radiation injuries, encouraging further research of this topic.« less
Power estimation using simulations for air pollution time-series studies
2012-01-01
Background Estimation of power to assess associations of interest can be challenging for time-series studies of the acute health effects of air pollution because there are two dimensions of sample size (time-series length and daily outcome counts), and because these studies often use generalized linear models to control for complex patterns of covariation between pollutants and time trends, meteorology and possibly other pollutants. In general, statistical software packages for power estimation rely on simplifying assumptions that may not adequately capture this complexity. Here we examine the impact of various factors affecting power using simulations, with comparison of power estimates obtained from simulations with those obtained using statistical software. Methods Power was estimated for various analyses within a time-series study of air pollution and emergency department visits using simulations for specified scenarios. Mean daily emergency department visit counts, model parameter value estimates and daily values for air pollution and meteorological variables from actual data (8/1/98 to 7/31/99 in Atlanta) were used to generate simulated daily outcome counts with specified temporal associations with air pollutants and randomly generated error based on a Poisson distribution. Power was estimated by conducting analyses of the association between simulated daily outcome counts and air pollution in 2000 data sets for each scenario. Power estimates from simulations and statistical software (G*Power and PASS) were compared. Results In the simulation results, increasing time-series length and average daily outcome counts both increased power to a similar extent. Our results also illustrate the low power that can result from using outcomes with low daily counts or short time series, and the reduction in power that can accompany use of multipollutant models. Power estimates obtained using standard statistical software were very similar to those from the simulations when properly implemented; implementation, however, was not straightforward. Conclusions These analyses demonstrate the similar impact on power of increasing time-series length versus increasing daily outcome counts, which has not previously been reported. Implementation of power software for these studies is discussed and guidance is provided. PMID:22995599
Power estimation using simulations for air pollution time-series studies.
Winquist, Andrea; Klein, Mitchel; Tolbert, Paige; Sarnat, Stefanie Ebelt
2012-09-20
Estimation of power to assess associations of interest can be challenging for time-series studies of the acute health effects of air pollution because there are two dimensions of sample size (time-series length and daily outcome counts), and because these studies often use generalized linear models to control for complex patterns of covariation between pollutants and time trends, meteorology and possibly other pollutants. In general, statistical software packages for power estimation rely on simplifying assumptions that may not adequately capture this complexity. Here we examine the impact of various factors affecting power using simulations, with comparison of power estimates obtained from simulations with those obtained using statistical software. Power was estimated for various analyses within a time-series study of air pollution and emergency department visits using simulations for specified scenarios. Mean daily emergency department visit counts, model parameter value estimates and daily values for air pollution and meteorological variables from actual data (8/1/98 to 7/31/99 in Atlanta) were used to generate simulated daily outcome counts with specified temporal associations with air pollutants and randomly generated error based on a Poisson distribution. Power was estimated by conducting analyses of the association between simulated daily outcome counts and air pollution in 2000 data sets for each scenario. Power estimates from simulations and statistical software (G*Power and PASS) were compared. In the simulation results, increasing time-series length and average daily outcome counts both increased power to a similar extent. Our results also illustrate the low power that can result from using outcomes with low daily counts or short time series, and the reduction in power that can accompany use of multipollutant models. Power estimates obtained using standard statistical software were very similar to those from the simulations when properly implemented; implementation, however, was not straightforward. These analyses demonstrate the similar impact on power of increasing time-series length versus increasing daily outcome counts, which has not previously been reported. Implementation of power software for these studies is discussed and guidance is provided.
Consideration of species community composition in statistical analyses of coral disease risk
Diseases are increasing in marine ecosystems, and these increases have been attributed to a number of environmental factors including climate change, pollution, and overfishing. However, many studies pool disease prevalence into taxonomic groups, disregarding host species compos...
Statistical Analyses of Raw Material Data for MTM45-1/CF7442A-36% RW: CMH Cure Cycle
NASA Technical Reports Server (NTRS)
Coroneos, Rula; Pai, Shantaram, S.; Murthy, Pappu
2013-01-01
This report describes statistical characterization of physical properties of the composite material system MTM45-1/CF7442A, which has been tested and is currently being considered for use on spacecraft structures. This composite system is made of 6K plain weave graphite fibers in a highly toughened resin system. This report summarizes the distribution types and statistical details of the tests and the conditions for the experimental data generated. These distributions will be used in multivariate regression analyses to help determine material and design allowables for similar material systems and to establish a procedure for other material systems. Additionally, these distributions will be used in future probabilistic analyses of spacecraft structures. The specific properties that are characterized are the ultimate strength, modulus, and Poisson??s ratio by using a commercially available statistical package. Results are displayed using graphical and semigraphical methods and are included in the accompanying appendixes.
Areepattamannil, Shaljan
2014-01-01
This study examined the relationships between academic motivation-intrinsic motivation, extrinsic motivation, amotivation-and mathematics achievement among 363 Indian adolescents in India and 355 Indian immigrant adolescents in Canada. Results of hierarchical multiple regression analyses showed that intrinsic motivation, extrinsic motivation, and amotivation were not statistically significantly related to mathematics achievement among Indian adolescents in India. In contrast, both intrinsic motivation and extrinsic motivation were statistically significantly related to mathematics achievement among Indian immigrant adolescents in Canada. While intrinsic motivation was a statistically significant positive predictor of mathematics achievement among Indian immigrant adolescents in Canada, extrinsic motivation was a statistically significant negative predictor of mathematics achievement among Indian immigrant adolescents in Canada. Amotivation was not statistically significantly related to mathematics achievement among Indian immigrant adolescents in Canada. Implications of the findings for pedagogy and practice are discussed.
A review of published analyses of case-cohort studies and recommendations for future reporting.
Sharp, Stephen J; Poulaliou, Manon; Thompson, Simon G; White, Ian R; Wood, Angela M
2014-01-01
The case-cohort study design combines the advantages of a cohort study with the efficiency of a nested case-control study. However, unlike more standard observational study designs, there are currently no guidelines for reporting results from case-cohort studies. Our aim was to review recent practice in reporting these studies, and develop recommendations for the future. By searching papers published in 24 major medical and epidemiological journals between January 2010 and March 2013 using PubMed, Scopus and Web of Knowledge, we identified 32 papers reporting case-cohort studies. The median subcohort sampling fraction was 4.1% (interquartile range 3.7% to 9.1%). The papers varied in their approaches to describing the numbers of individuals in the original cohort and the subcohort, presenting descriptive data, and in the level of detail provided about the statistical methods used, so it was not always possible to be sure that appropriate analyses had been conducted. Based on the findings of our review, we make recommendations about reporting of the study design, subcohort definition, numbers of participants, descriptive information and statistical methods, which could be used alongside existing STROBE guidelines for reporting observational studies.
Designing Intervention Studies: Selected Populations, Range Restrictions, and Statistical Power
Miciak, Jeremy; Taylor, W. Pat; Stuebing, Karla K.; Fletcher, Jack M.; Vaughn, Sharon
2016-01-01
An appropriate estimate of statistical power is critical for the design of intervention studies. Although the inclusion of a pretest covariate in the test of the primary outcome can increase statistical power, samples selected on the basis of pretest performance may demonstrate range restriction on the selection measure and other correlated measures. This can result in attenuated pretest-posttest correlations, reducing the variance explained by the pretest covariate. We investigated the implications of two potential range restriction scenarios: direct truncation on a selection measure and indirect range restriction on correlated measures. Empirical and simulated data indicated direct range restriction on the pretest covariate greatly reduced statistical power and necessitated sample size increases of 82%–155% (dependent on selection criteria) to achieve equivalent statistical power to parameters with unrestricted samples. However, measures demonstrating indirect range restriction required much smaller sample size increases (32%–71%) under equivalent scenarios. Additional analyses manipulated the correlations between measures and pretest-posttest correlations to guide planning experiments. Results highlight the need to differentiate between selection measures and potential covariates and to investigate range restriction as a factor impacting statistical power. PMID:28479943
Designing Intervention Studies: Selected Populations, Range Restrictions, and Statistical Power.
Miciak, Jeremy; Taylor, W Pat; Stuebing, Karla K; Fletcher, Jack M; Vaughn, Sharon
2016-01-01
An appropriate estimate of statistical power is critical for the design of intervention studies. Although the inclusion of a pretest covariate in the test of the primary outcome can increase statistical power, samples selected on the basis of pretest performance may demonstrate range restriction on the selection measure and other correlated measures. This can result in attenuated pretest-posttest correlations, reducing the variance explained by the pretest covariate. We investigated the implications of two potential range restriction scenarios: direct truncation on a selection measure and indirect range restriction on correlated measures. Empirical and simulated data indicated direct range restriction on the pretest covariate greatly reduced statistical power and necessitated sample size increases of 82%-155% (dependent on selection criteria) to achieve equivalent statistical power to parameters with unrestricted samples. However, measures demonstrating indirect range restriction required much smaller sample size increases (32%-71%) under equivalent scenarios. Additional analyses manipulated the correlations between measures and pretest-posttest correlations to guide planning experiments. Results highlight the need to differentiate between selection measures and potential covariates and to investigate range restriction as a factor impacting statistical power.
Meta-analysis of thirty-two case-control and two ecological radon studies of lung cancer.
Dobrzynski, Ludwik; Fornalski, Krzysztof W; Reszczynska, Joanna
2018-03-01
A re-analysis has been carried out of thirty-two case-control and two ecological studies concerning the influence of radon, a radioactive gas, on the risk of lung cancer. Three mathematically simplest dose-response relationships (models) were tested: constant (zero health effect), linear, and parabolic (linear-quadratic). Health effect end-points reported in the analysed studies are odds ratios or relative risk ratios, related either to morbidity or mortality. In our preliminary analysis, we show that the results of dose-response fitting are qualitatively (within uncertainties, given as error bars) the same, whichever of these health effect end-points are applied. Therefore, we deemed it reasonable to aggregate all response data into the so-called Relative Health Factor and jointly analysed such mixed data, to obtain better statistical power. In the second part of our analysis, robust Bayesian and classical methods of analysis were applied to this combined dataset. In this part of our analysis, we selected different subranges of radon concentrations. In view of substantial differences between the methodology used by the authors of case-control and ecological studies, the mathematical relationships (models) were applied mainly to the thirty-two case-control studies. The degree to which the two ecological studies, analysed separately, affect the overall results when combined with the thirty-two case-control studies, has also been evaluated. In all, as a result of our meta-analysis of the combined cohort, we conclude that the analysed data concerning radon concentrations below ~1000 Bq/m3 (~20 mSv/year of effective dose to the whole body) do not support the thesis that radon may be a cause of any statistically significant increase in lung cancer incidence.
Samanta, Brajogopal; Bhadury, Punyasloke
2016-01-01
Marine chromophytes are taxonomically diverse group of algae and contribute approximately half of the total oceanic primary production. To understand the global patterns of functional diversity of chromophytic phytoplankton, robust bioinformatics and statistical analyses including deep phylogeny based on 2476 form ID rbcL gene sequences representing seven ecologically significant oceanographic ecoregions were undertaken. In addition, 12 form ID rbcL clone libraries were generated and analyzed (148 sequences) from Sundarbans Biosphere Reserve representing the world’s largest mangrove ecosystem as part of this study. Global phylogenetic analyses recovered 11 major clades of chromophytic phytoplankton in varying proportions with several novel rbcL sequences in each of the seven targeted ecoregions. Majority of OTUs was found to be exclusive to each ecoregion, whereas some were shared by two or more ecoregions based on beta-diversity analysis. Present phylogenetic and bioinformatics analyses provide a strong statistical support for the hypothesis that different oceanographic regimes harbor distinct and coherent groups of chromophytic phytoplankton. It has been also shown as part of this study that varying natural selection pressure on form ID rbcL gene under different environmental conditions could lead to functional differences and overall fitness of chromophytic phytoplankton populations. PMID:26861415
Neman, R
1975-03-01
The Zigler and Seitz (1975) critique was carefully examined with respect to the conclusions of the Neman et al. (1975) study. Particular attention was given to the following questions: (a) did experimenter bias or commitment account for the results, (b) were unreliable and invalid psychometric instruments used, (c) were the statistical analyses insufficient or incorrect, (d) did the results reflect no more than the operation of chance, and (e) were the results biased by artifactually inflated profile scores. Experimenter bias and commitment were shown to be insufficient to account for the results; a further review of Buros (1972) showed that there was no need for apprehension about the testing instruments; the statistical analyses were shown to exceed prevailing standards for research reporting; the results were shown to reflect valid findings at the .05 probability level; and the Neman et al. (1975) results for the profile measure were equally significant using either "raw" neurological scores or "scales" neurological age scores. Zigler, Seitz, and I agreed on the needs for (a) using multivariate analyses, where applicable, in studies having more than one dependent variable; (b) defining the population for which sensorimotor training procedures may be appropriately prescribed; and (c) validating the profile measure as a tool to assess neurological disorganization.
Hashim, Muhammad Jawad
2010-09-01
Post-hoc secondary data analysis with no prespecified hypotheses has been discouraged by textbook authors and journal editors alike. Unfortunately no single term describes this phenomenon succinctly. I would like to coin the term "sigsearch" to define this practice and bring it within the teaching lexicon of statistics courses. Sigsearch would include any unplanned, post-hoc search for statistical significance using multiple comparisons of subgroups. It would also include data analysis with outcomes other than the prespecified primary outcome measure of a study as well as secondary data analyses of earlier research.
Crimes against the elderly in Italy, 2007-2014.
Terranova, Claudio; Bevilacqua, Greta; Zen, Margherita; Montisci, Massimo
2017-08-01
Crimes against the elderly have physical, psychological, and economic consequences. Approaches for mitigating them must be based on comprehensive knowledge of the phenomenon. This study analyses crimes against the elderly in Italy during the period 2007-2014 from an epidemiological viewpoint. Data on violent and non-violent crimes derived from the Italian Institute of Statistics were analysed in relation to trends, gender and age by linear regression, T-test, and calculation of the odds ratio with a 95% confidence interval. Results show that the elderly are at higher risk of being victimized in two types of crime, violent (residential robbery) and non-violent (pick-pocketing and purse-snatching) compared with other age groups during the period considered. A statistically significant increase in residential robbery and pick-pocketing was also observed. The rate of homicide against the elderly was stable during the study period, in contrast with reduced rates in other age groups. These results may be explained by risk factors increasing the profiles of elderly individuals as potential victims, such as frailty, cognitive impairment, and social isolation. Further studies analysing the characteristics of victims are required. Based on the results presented here, appropriate preventive strategies should be planned to reduce crimes against the elderly. Copyright © 2017 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.
Emprechtinger, Robert; Piso, Brigitte; Ringleb, Peter A
2017-03-01
Mechanical thrombectomy with stent retrievers is an effective treatment for patients with ischemic stroke. Results of recent meta-analyses report that the treatment is safe. However, the endpoints recurrent stroke, vasospasms, and subarachnoid hemorrhage have not been evaluated sufficiently. Hence, we extracted data on these outcomes from the five recent thrombectomy trials (MR CLEAN, ESCAPE, REVASCAT, SWIFT PRIME, and EXTEND IA published in 2015). Subsequently, we conducted meta-analyses for each outcome. We report the results of the fixed, as well as the random effects model. Three studies reported data on recurrent strokes. While the results did not reach statistical significance in the random effects model (despite a three times elevated risk), the fixed effects model revealed a significantly higher rate of recurrent strokes after thrombectomy. Four studies reported data on subarachnoid hemorrhage. The higher pooled rates in the intervention groups were statistically significant in both, the fixed and the random effects model. One study reported on vasospasms. We recorded 14 events in the intervention group and none in the control group. The efficacy of mechanical thrombectomy is not questioned, yet our results indicate an increased risk for recurrent strokes, subarachnoid hemorrhage, and vasospasms post-treatment. Therefore, we strongly recommend a thoroughly surveillance, concerning these adverse events in future clinical trials and routine registries.
NASA Astrophysics Data System (ADS)
Alshipli, Marwan; Kabir, Norlaili A.
2017-05-01
Computed tomography (CT) employs X-ray radiation to create cross-sectional images. Dual-energy CT acquisition includes the images acquired from an alternating voltage of X-ray tube: a low- and a high-peak kilovoltage. The main objective of this study is to determine the best slice thickness that reduces image noise with adequate diagnostic information using dual energy CT head protocol. The study used the ImageJ software and statistical analyses to aid the medical image analysis of dual-energy CT. In this study, ImageJ software and F-test were utilised as the combination methods to analyse DICOM CT images. They were used to investigate the effect of slice thickness on noise and visibility in dual-energy CT head protocol images. Catphan-600 phantom was scanned at different slice thickness values;.6, 1, 2, 3, 4, 5 and 6 mm, then quantitative analyses were carried out. The DECT operated in helical mode with another fixed scan parameter values. Based on F-test statistical analyses, image noise at 0.6, 1, and 2 mm were significantly different compared to the other images acquired at slice thickness of 3, 4, 5, and 6 mm. However, no significant differences of image noise were observed at 3, 4, 5, and 6 mm. As a result, better diagnostic image value, image visibility, and lower image noise in dual-energy CT head protocol was observed at a slice thickness of 3 mm.
ERIC Educational Resources Information Center
Yaman, Hakan; Dündar, Sefa; Ayvaz, Ülkü
2015-01-01
The aim of this study is to reveal whether there is relation between achievement motivations of teacher candidates according to their cognitive styles and motivation styles or not. This study was designed as a quantitative study due to collecting quantitative data and running statistical analyses. Both comparative and correlational survey methods…
Computer Access and Computer Use for Science Performance of Racial and Linguistic Minority Students
ERIC Educational Resources Information Center
Chang, Mido; Kim, Sunha
2009-01-01
This study examined the effects of computer access and computer use on the science achievement of elementary school students, with focused attention on the effects for racial and linguistic minority students. The study used the Early Childhood Longitudinal Study (ECLS-K) database and conducted statistical analyses with proper weights and…
Three Studies on the Leadership Behaviors of Academic Deans in Higher Education
ERIC Educational Resources Information Center
Brower, Rebecca
2013-01-01
This three article mixed methods dissertation is titled "Three Studies on the Leadership Behaviors of Academic Deans in Higher Education." Each article is based on a sample of 51 academic deans from a three state region in the Southeastern United States. In the first study, the results of the statistical analyses reinforce the gender…
Parental Socio-Economic Status as Correlate of Child Labour in Ile-Ife, Nigeria
ERIC Educational Resources Information Center
Elegbeleye, O. S.; Olasupo, M. O.
2012-01-01
This study investigated the relationship between parental socio-economic status and child labour practices in Ile-Ife, Nigeria. The study employed survey method to gather data from 200 parents which constituted the study population. Pearson Product Moment Correlation and t-test statistics were used for the data analyses. The outcome of the study…
Varma, Rajesh; Gupta, Janesh K
2006-01-01
There is considerable evidence to show an association between genital tract infections, such as bacterial vaginosis (BV), and preterm delivery (PTD). Meta-analyses to date have shown screening and treating BV in pregnancy does not prevent PTD. This casts doubt on a cause and effect relationship between BV and PTD. However, the meta-analyses reported significant clinical, methodological and statistical heterogeneity of the included studies. We therefore undertook a repeat meta-analysis, included recently published trials, and applied strict criteria on data extraction. We meta-analysed low and high-risk pregnancies separately. We found that screening and treating BV in low-risk pregnancies produced a statistically significant reduction in spontaneous PTD (RR 0.73; 95% CI 0.55-0.98). This beneficial effect was not observed in high-risk or combined risk groups. The differences in antibiotic sensitivity between high and low risk groups may suggest differing causal contributions of the infectious process to PTD. The evidence, along with prior knowledge of differing predisposing factors and prognosis between these risk groups, supports the hypothesis that PTD in high and low risk pregnant women are different entities and not linear extremes of the same syndrome.
Pereira, Tiago Veiga; Rudnicki, Martina; Pereira, Alexandre Costa; Pombo-de-Oliveira, Maria S; Franco, Rendrik França
2006-01-01
Meta-analysis has become an important statistical tool in genetic association studies, since it may provide more powerful and precise estimates. However, meta-analytic studies are prone to several potential biases not only because the preferential publication of "positive'' studies but also due to difficulties in obtaining all relevant information during the study selection process. In this letter, we point out major problems in meta-analysis that may lead to biased conclusions, illustrating an empirical example of two recent meta-analyses on the relation between MTHFR polymorphisms and risk of acute lymphoblastic leukemia that, despite the similarity in statistical methods and period of study selection, provided partially conflicting results.
Winer, E Samuel; Cervone, Daniel; Bryant, Jessica; McKinney, Cliff; Liu, Richard T; Nadorff, Michael R
2016-09-01
A popular way to attempt to discern causality in clinical psychology is through mediation analysis. However, mediation analysis is sometimes applied to research questions in clinical psychology when inferring causality is impossible. This practice may soon increase with new, readily available, and easy-to-use statistical advances. Thus, we here provide a heuristic to remind clinical psychological scientists of the assumptions of mediation analyses. We describe recent statistical advances and unpack assumptions of causality in mediation, underscoring the importance of time in understanding mediational hypotheses and analyses in clinical psychology. Example analyses demonstrate that statistical mediation can occur despite theoretical mediation being improbable. We propose a delineation of mediational effects derived from cross-sectional designs into the terms temporal and atemporal associations to emphasize time in conceptualizing process models in clinical psychology. The general implications for mediational hypotheses and the temporal frameworks from within which they may be drawn are discussed. © 2016 Wiley Periodicals, Inc.
Multivariate statistical analysis of low-voltage EDS spectrum images
DOE Office of Scientific and Technical Information (OSTI.GOV)
Anderson, I.M.
1998-03-01
Whereas energy-dispersive X-ray spectrometry (EDS) has been used for compositional analysis in the scanning electron microscope for 30 years, the benefits of using low operating voltages for such analyses have been explored only during the last few years. This paper couples low-voltage EDS with two other emerging areas of characterization: spectrum imaging and multivariate statistical analysis. The specimen analyzed for this study was a finished Intel Pentium processor, with the polyimide protective coating stripped off to expose the final active layers.
This tool allows users to animate cancer trends over time by cancer site and cause of death, race, and sex. Provides access to incidence, mortality, and survival. Select the type of statistic, variables, format, and then extract the statistics in a delimited format for further analyses.
MWASTools: an R/bioconductor package for metabolome-wide association studies.
Rodriguez-Martinez, Andrea; Posma, Joram M; Ayala, Rafael; Neves, Ana L; Anwar, Maryam; Petretto, Enrico; Emanueli, Costanza; Gauguier, Dominique; Nicholson, Jeremy K; Dumas, Marc-Emmanuel
2018-03-01
MWASTools is an R package designed to provide an integrated pipeline to analyse metabonomic data in large-scale epidemiological studies. Key functionalities of our package include: quality control analysis; metabolome-wide association analysis using various models (partial correlations, generalized linear models); visualization of statistical outcomes; metabolite assignment using statistical total correlation spectroscopy (STOCSY); and biological interpretation of metabolome-wide association studies results. The MWASTools R package is implemented in R (version > =3.4) and is available from Bioconductor: https://bioconductor.org/packages/MWASTools/. m.dumas@imperial.ac.uk. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.
Fast and accurate imputation of summary statistics enhances evidence of functional enrichment
Pasaniuc, Bogdan; Zaitlen, Noah; Shi, Huwenbo; Bhatia, Gaurav; Gusev, Alexander; Pickrell, Joseph; Hirschhorn, Joel; Strachan, David P.; Patterson, Nick; Price, Alkes L.
2014-01-01
Motivation: Imputation using external reference panels (e.g. 1000 Genomes) is a widely used approach for increasing power in genome-wide association studies and meta-analysis. Existing hidden Markov models (HMM)-based imputation approaches require individual-level genotypes. Here, we develop a new method for Gaussian imputation from summary association statistics, a type of data that is becoming widely available. Results: In simulations using 1000 Genomes (1000G) data, this method recovers 84% (54%) of the effective sample size for common (>5%) and low-frequency (1–5%) variants [increasing to 87% (60%) when summary linkage disequilibrium information is available from target samples] versus the gold standard of 89% (67%) for HMM-based imputation, which cannot be applied to summary statistics. Our approach accounts for the limited sample size of the reference panel, a crucial step to eliminate false-positive associations, and it is computationally very fast. As an empirical demonstration, we apply our method to seven case–control phenotypes from the Wellcome Trust Case Control Consortium (WTCCC) data and a study of height in the British 1958 birth cohort (1958BC). Gaussian imputation from summary statistics recovers 95% (105%) of the effective sample size (as quantified by the ratio of χ2 association statistics) compared with HMM-based imputation from individual-level genotypes at the 227 (176) published single nucleotide polymorphisms (SNPs) in the WTCCC (1958BC height) data. In addition, for publicly available summary statistics from large meta-analyses of four lipid traits, we publicly release imputed summary statistics at 1000G SNPs, which could not have been obtained using previously published methods, and demonstrate their accuracy by masking subsets of the data. We show that 1000G imputation using our approach increases the magnitude and statistical evidence of enrichment at genic versus non-genic loci for these traits, as compared with an analysis without 1000G imputation. Thus, imputation of summary statistics will be a valuable tool in future functional enrichment analyses. Availability and implementation: Publicly available software package available at http://bogdan.bioinformatics.ucla.edu/software/. Contact: bpasaniuc@mednet.ucla.edu or aprice@hsph.harvard.edu Supplementary information: Supplementary materials are available at Bioinformatics online. PMID:24990607
Klaus, Jana; Schutter, Dennis J L G
2018-06-01
Non-invasive brain stimulation (NIBS) has become a common method to study the interrelations between the brain and language functioning. This meta-analysis examined the efficacy of transcranial magnetic stimulation (TMS) and direct current stimulation (tDCS) in the study of language production in healthy volunteers. Forty-five effect sizes from 30 studies which investigated the effects of NIBS on picture naming or verbal fluency in healthy participants were meta-analysed. Further sub-analyses investigated potential influences of stimulation type, control, target site, task, online vs. offline application, and current density of the target electrode. Random effects modelling showed a small, but reliable effect of NIBS on language production. Subsequent analyses indicated larger weighted mean effect sizes for TMS as compared to tDCS studies. No statistical differences for the other sub-analyses were observed. We conclude that NIBS is a useful method for neuroscientific studies on language production in healthy volunteers. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
2008-01-01
There is an increasing need for students in the biological sciences to build a strong foundation in quantitative approaches to data analyses. Although most science, engineering, and math field majors are required to take at least one statistics course, statistical analysis is poorly integrated into undergraduate biology course work, particularly at the lower-division level. Elements of statistics were incorporated into an introductory biology course, including a review of statistics concepts and opportunity for students to perform statistical analysis in a biological context. Learning gains were measured with an 11-item statistics learning survey instrument developed for the course. Students showed a statistically significant 25% (p < 0.005) increase in statistics knowledge after completing introductory biology. Students improved their scores on the survey after completing introductory biology, even if they had previously completed an introductory statistics course (9%, improvement p < 0.005). Students retested 1 yr after completing introductory biology showed no loss of their statistics knowledge as measured by this instrument, suggesting that the use of statistics in biology course work may aid long-term retention of statistics knowledge. No statistically significant differences in learning were detected between male and female students in the study. PMID:18765754
Investigation of Primary Mathematics Student Teachers' Concept Images: Cylinder and Cone
ERIC Educational Resources Information Center
Ertekin, Erhan; Yazici, Ersen; Delice, Ali
2014-01-01
The aim of the present study is to determine the influence of concept definitions of cylinder and cone on primary mathematics student teachers' construction of relevant concept images. The study had a relational survey design and the participants were 238 primary mathematics student teachers. Statistical analyses implied the following: mathematics…
Basic School Teachers' Perceptions about Curriculum Design in Ghana
ERIC Educational Resources Information Center
Abudu, Amadu Musah; Mensah, Mary Afi
2016-01-01
This study focused on teachers' perceptions about curriculum design and barriers to their participation. The sample size was 130 teachers who responded to a questionnaire. The analyses made use of descriptive statistics and descriptions. The study found that the level of teachers' participation in curriculum design is low. The results further…
ERIC Educational Resources Information Center
Mohr-Schroeder, Margaret J.; Jackson, Christa; Cavalcanti, Maureen; Jong, Cindy; Schroeder, D. Craig; Speler, Lydia G.
2017-01-01
The purpose of this study was to investigate parents' attitudes toward mathematics, their students' attitude toward mathematics, and the influence of the parents' attitude on the students' attitude toward mathematics. Data analyses revealed statistically significant positive correlations between parents' and students' attitudes toward mathematics.…
Open Doors 1991/92. Report on International Educational Exchange.
ERIC Educational Resources Information Center
Zikopoulos, Marianthi, Ed.; And Others
1992-01-01
This report provides statistical data on 419,600 foreign students from over 200 countries studying at U.S. higher educational institutions. The report identifies trends in student mobility and migration, national origin, sources of financial support, fields of study, enrollments, and rates of growth. The book's extensive tables and analyses are…
Statistics for X-chromosome associations.
Özbek, Umut; Lin, Hui-Min; Lin, Yan; Weeks, Daniel E; Chen, Wei; Shaffer, John R; Purcell, Shaun M; Feingold, Eleanor
2018-06-13
In a genome-wide association study (GWAS), association between genotype and phenotype at autosomal loci is generally tested by regression models. However, X-chromosome data are often excluded from published analyses of autosomes because of the difference between males and females in number of X chromosomes. Failure to analyze X-chromosome data at all is obviously less than ideal, and can lead to missed discoveries. Even when X-chromosome data are included, they are often analyzed with suboptimal statistics. Several mathematically sensible statistics for X-chromosome association have been proposed. The optimality of these statistics, however, is based on very specific simple genetic models. In addition, while previous simulation studies of these statistics have been informative, they have focused on single-marker tests and have not considered the types of error that occur even under the null hypothesis when the entire X chromosome is scanned. In this study, we comprehensively tested several X-chromosome association statistics using simulation studies that include the entire chromosome. We also considered a wide range of trait models for sex differences and phenotypic effects of X inactivation. We found that models that do not incorporate a sex effect can have large type I error in some cases. We also found that many of the best statistics perform well even when there are modest deviations, such as trait variance differences between the sexes or small sex differences in allele frequencies, from assumptions. © 2018 WILEY PERIODICALS, INC.
Multiple Phenotype Association Tests Using Summary Statistics in Genome-Wide Association Studies
Liu, Zhonghua; Lin, Xihong
2017-01-01
Summary We study in this paper jointly testing the associations of a genetic variant with correlated multiple phenotypes using the summary statistics of individual phenotype analysis from Genome-Wide Association Studies (GWASs). We estimated the between-phenotype correlation matrix using the summary statistics of individual phenotype GWAS analyses, and developed genetic association tests for multiple phenotypes by accounting for between-phenotype correlation without the need to access individual-level data. Since genetic variants often affect multiple phenotypes differently across the genome and the between-phenotype correlation can be arbitrary, we proposed robust and powerful multiple phenotype testing procedures by jointly testing a common mean and a variance component in linear mixed models for summary statistics. We computed the p-values of the proposed tests analytically. This computational advantage makes our methods practically appealing in large-scale GWASs. We performed simulation studies to show that the proposed tests maintained correct type I error rates, and to compare their powers in various settings with the existing methods. We applied the proposed tests to a GWAS Global Lipids Genetics Consortium summary statistics data set and identified additional genetic variants that were missed by the original single-trait analysis. PMID:28653391
Multiple phenotype association tests using summary statistics in genome-wide association studies.
Liu, Zhonghua; Lin, Xihong
2018-03-01
We study in this article jointly testing the associations of a genetic variant with correlated multiple phenotypes using the summary statistics of individual phenotype analysis from Genome-Wide Association Studies (GWASs). We estimated the between-phenotype correlation matrix using the summary statistics of individual phenotype GWAS analyses, and developed genetic association tests for multiple phenotypes by accounting for between-phenotype correlation without the need to access individual-level data. Since genetic variants often affect multiple phenotypes differently across the genome and the between-phenotype correlation can be arbitrary, we proposed robust and powerful multiple phenotype testing procedures by jointly testing a common mean and a variance component in linear mixed models for summary statistics. We computed the p-values of the proposed tests analytically. This computational advantage makes our methods practically appealing in large-scale GWASs. We performed simulation studies to show that the proposed tests maintained correct type I error rates, and to compare their powers in various settings with the existing methods. We applied the proposed tests to a GWAS Global Lipids Genetics Consortium summary statistics data set and identified additional genetic variants that were missed by the original single-trait analysis. © 2017, The International Biometric Society.
ISSUES IN THE STATISTICAL ANALYSIS OF SMALL-AREA HEALTH DATA. (R825173)
The availability of geographically indexed health and population data, with advances in computing, geographical information systems and statistical methodology, have opened the way for serious exploration of small area health statistics based on routine data. Such analyses may be...
Hardell, Elin; Carlberg, Michael; Nordström, Marie; van Bavel, Bert
2010-09-15
Persistent organic pollutants (POPs) are lipophilic chemicals that bioaccumulate. Most of them were resticted or banned in the 1970s and 1980s to protect human health and the environment. The main source for humans is dietary intake of dairy products, meat and fish. Little data exist on changes of the concentration of POPs in the Swedish population over time. To study if the concentrations of polychlorinated biphenyls (PCBs), DDE, hexachlorobenzene (HCB) and chlordanes have changed in the Swedish population during 1993-2007, and certain factors that may influence the concentrations. During 1993-2007 samples from 537 controls in different human cancer studies were collected and analysed. Background information such as body mass index, breast-feeding and parity was assessed by questionaires. Wilcoxon rank-sum test was used to analyse the explanatory factors specimen (blood or adipose tissue), gender, BMI, total breast-feeding and parity in relation to POPs. Time trends for POPs were analysed using linear regression analysis, adjusted for specimen, gender, BMI and age. The concentration decreased for all POPs during 1993-2007. The annual change was statistically significant for the sum of PCBs -7.2%, HCB -8.8%, DDE -13.5% and the sum of chlordanes -10.3%. BMI and age were determinants of the concentrations. Cumulative breast-feeding >8 months gave statistically significantly lower concentrations for the sum of PCBs, DDE and the sum of chlordanes. Parity with >2 children yielded statistically significantly lower sum of PCBs. All the studied POPs decreased during the time period, probably due to restrictions of their use. Copyright 2010 Elsevier B.V. All rights reserved.
Statistical analyses of the relative risk.
Gart, J J
1979-01-01
Let P1 be the probability of a disease in one population and P2 be the probability of a disease in a second population. The ratio of these quantities, R = P1/P2, is termed the relative risk. We consider first the analyses of the relative risk from retrospective studies. The relation between the relative risk and the odds ratio (or cross-product ratio) is developed. The odds ratio can be considered a parameter of an exponential model possessing sufficient statistics. This permits the development of exact significance tests and confidence intervals in the conditional space. Unconditional tests and intervals are also considered briefly. The consequences of misclassification errors and ignoring matching or stratifying are also considered. The various methods are extended to combination of results over the strata. Examples of case-control studies testing the association between HL-A frequencies and cancer illustrate the techniques. The parallel analyses of prospective studies are given. If P1 and P2 are small with large samples sizes the appropriate model is a Poisson distribution. This yields a exponential model with sufficient statistics. Exact conditional tests and confidence intervals can then be developed. Here we consider the case where two populations are compared adjusting for sex differences as well as for the strata (or covariate) differences such as age. The methods are applied to two examples: (1) testing in the two sexes the ratio of relative risks of skin cancer in people living in different latitudes, and (2) testing over time the ratio of the relative risks of cancer in two cities, one of which fluoridated its drinking water and one which did not. PMID:540589
Separate-channel analysis of two-channel microarrays: recovering inter-spot information.
Smyth, Gordon K; Altman, Naomi S
2013-05-26
Two-channel (or two-color) microarrays are cost-effective platforms for comparative analysis of gene expression. They are traditionally analysed in terms of the log-ratios (M-values) of the two channel intensities at each spot, but this analysis does not use all the information available in the separate channel observations. Mixed models have been proposed to analyse intensities from the two channels as separate observations, but such models can be complex to use and the gain in efficiency over the log-ratio analysis is difficult to quantify. Mixed models yield test statistics for the null distributions can be specified only approximately, and some approaches do not borrow strength between genes. This article reformulates the mixed model to clarify the relationship with the traditional log-ratio analysis, to facilitate information borrowing between genes, and to obtain an exact distributional theory for the resulting test statistics. The mixed model is transformed to operate on the M-values and A-values (average log-expression for each spot) instead of on the log-expression values. The log-ratio analysis is shown to ignore information contained in the A-values. The relative efficiency of the log-ratio analysis is shown to depend on the size of the intraspot correlation. A new separate channel analysis method is proposed that assumes a constant intra-spot correlation coefficient across all genes. This approach permits the mixed model to be transformed into an ordinary linear model, allowing the data analysis to use a well-understood empirical Bayes analysis pipeline for linear modeling of microarray data. This yields statistically powerful test statistics that have an exact distributional theory. The log-ratio, mixed model and common correlation methods are compared using three case studies. The results show that separate channel analyses that borrow strength between genes are more powerful than log-ratio analyses. The common correlation analysis is the most powerful of all. The common correlation method proposed in this article for separate-channel analysis of two-channel microarray data is no more difficult to apply in practice than the traditional log-ratio analysis. It provides an intuitive and powerful means to conduct analyses and make comparisons that might otherwise not be possible.
Overweight, but not obesity, paradox on mortality following coronary artery bypass grafting.
Takagi, Hisato; Umemoto, Takuya
2016-09-01
To determine whether an "obesity paradox" on post-coronary artery bypass grafting (CABG) mortality exists, we abstracted exclusively adjusted odds ratios (ORs) and/or hazard ratios (HRs) for mortality from each study, and then combined them in a meta-analysis. MEDLINE and EMBASE were searched through April 2015 using PubMed and OVID, to identify comparative studies, of overweight or obese versus normal weight patients undergoing CABG, reporting adjusted relative risk estimates for short-term (30-day or in-hospital) and/or mid-to-long-term all-cause mortality. Our search identified 14 eligible studies. In total our meta-analysis included data on 79,140 patients undergoing CABG. Pooled analyses in short-term mortality demonstrated that overweight was associated with a statistically significant 15% reduction relative to normal weight (OR, 0.85; 95% confidence interval [CI], 0.74-0.98; p=0.03) and no statistically significant differences between mild obesity, moderate/severe obesity, or overall obesity and normal weight. Pooled analyses in mid-to-long-term mortality demonstrated that overweight was associated with a statistically significant 10% reduction relative to normal weight (HR, 0.90; 95% CI, 0.84 to 0.96; p=0.001); and no statistically significant differences between mild obesity, moderate/severe obesity, or overall obesity and normal weight. Overweight, but not obesity, may be associated with better short-term and mid-to-long-term post-CABG survival relative to normal weight. An overweight, but not obesity, paradox on post-CABG mortality appears to exist. Copyright © 2015 Japanese College of Cardiology. Published by Elsevier Ltd. All rights reserved.
Patton, Charles J.; Kryskalla, Jennifer R.
2011-01-01
In addition to operational details and performance benchmarks for these new DA-AtNaR2 nitrate + nitrite assays, this report also provides results of interference studies for common inorganic and organic matrix constituents at 1, 10, and 100 times their median concentrations in surface-water and groundwater samples submitted annually to the NWQL for nitrate + nitrite analyses. Paired t-test and Wilcoxon signed-rank statistical analyses of results determined by CFA-CdR methods and DA-AtNaR2 methods indicate that nitrate concentration differences between population means or sign ranks were either statistically equivalent to zero at the 95 percent confidence level (p ≥ 0.05) or analytically equivalent to zero-that is, when p < 0.05, concentration differences between population means or medians were less than MDLs.
Impact of animal health programmes on poverty reduction and sustainable livestock development.
Pradere, J P
2017-04-01
Based on data from publications and field observations, this study analyses the interactions between animal health, rural poverty and the performance and environmental impact of livestock farming in low-income countries and middle-income countries. There are strong statistical correlations between the quality of Veterinary Services, livestock productivity and poverty rates. In countries with effective Veterinary Services, livestock growth stems mainly from productivity gains and poverty rates are the lowest. Conversely, these analyses identify no statistical link between the quality of Veterinary Services and increased livestock production volumes. However, where animal diseases are poorly controlled, productivity is low and livestock growth is extensive, based mainly on a steady increase in animal numbers. Extensive growth is less effective than intensive growth in reducing poverty and aggravates the pressure of livestock production on natural resources and the climate.
Akifuddin, Syed; Khatoon, Farheen
2015-12-01
Health care faces challenges due to complications, inefficiencies and other concerns that threaten the safety of patients. The purpose of his study was to identify causes of complications encountered after administration of local anaesthesia for dental and oral surgical procedures and to reduce the incidence of complications by introduction of six sigma methodology. DMAIC (Define, Measure, Analyse, Improve and Control) process of Six Sigma was taken into consideration to reduce the incidence of complications encountered after administration of local anaesthesia injections for dental and oral surgical procedures using failure mode and effect analysis. Pareto analysis was taken into consideration to analyse the most recurring complications. Paired z-sample test using Minitab Statistical Inference and Fisher's exact test was used to statistically analyse the obtained data. The p-value <0.05 was considered as significant value. Total 54 systemic and 62 local complications occurred during three months of analyse and measure phase. Syncope, failure of anaesthesia, trismus, auto mordeduras and pain at injection site was found to be most recurring complications. Cumulative defective percentage was 7.99 in case of pre-improved data and decreased to 4.58 in the control phase. Estimate for difference was 0.0341228 and 95% lower bound for difference was 0.0193966. p-value was found to be highly significant with p= 0.000. The application of six sigma improvement methodology in healthcare tends to deliver consistently better results to the patients as well as hospitals and results in better patient compliance as well as satisfaction.
Mediation Analysis with Survival Outcomes: Accelerated Failure Time vs. Proportional Hazards Models
Gelfand, Lois A.; MacKinnon, David P.; DeRubeis, Robert J.; Baraldi, Amanda N.
2016-01-01
Objective: Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and contain unobserved (censored) events. We present considerations for choosing an approach, using a comparison of semi-parametric proportional hazards (PH) and fully parametric accelerated failure time (AFT) approaches for illustration. Method: We compare PH and AFT models and procedures in their integration into mediation models and review their ability to produce coefficients that estimate causal effects. Using simulation studies modeling Weibull-distributed survival times, we compare statistical properties of mediation analyses incorporating PH and AFT approaches (employing SAS procedures PHREG and LIFEREG, respectively) under varied data conditions, some including censoring. A simulated data set illustrates the findings. Results: AFT models integrate more easily than PH models into mediation models. Furthermore, mediation analyses incorporating LIFEREG produce coefficients that can estimate causal effects, and demonstrate superior statistical properties. Censoring introduces bias in the coefficient estimate representing the treatment effect on outcome—underestimation in LIFEREG, and overestimation in PHREG. With LIFEREG, this bias can be addressed using an alternative estimate obtained from combining other coefficients, whereas this is not possible with PHREG. Conclusions: When Weibull assumptions are not violated, there are compelling advantages to using LIFEREG over PHREG for mediation analyses involving survival-time outcomes. Irrespective of the procedures used, the interpretation of coefficients, effects of censoring on coefficient estimates, and statistical properties should be taken into account when reporting results. PMID:27065906
DOE Office of Scientific and Technical Information (OSTI.GOV)
Metoyer, Candace N.; Walsh, Stephen J.; Tardiff, Mark F.
2008-10-30
The detection and identification of weak gaseous plumes using thermal imaging data is complicated by many factors. These include variability due to atmosphere, ground and plume temperature, and background clutter. This paper presents an analysis of one formulation of the physics-based model that describes the at-sensor observed radiance. The motivating question for the analyses performed in this paper is as follows. Given a set of backgrounds, is there a way to predict the background over which the probability of detecting a given chemical will be the highest? Two statistics were developed to address this question. These statistics incorporate data frommore » the long-wave infrared band to predict the background over which chemical detectability will be the highest. These statistics can be computed prior to data collection. As a preliminary exploration into the predictive ability of these statistics, analyses were performed on synthetic hyperspectral images. Each image contained one chemical (either carbon tetrachloride or ammonia) spread across six distinct background types. The statistics were used to generate predictions for the background ranks. Then, the predicted ranks were compared to the empirical ranks obtained from the analyses of the synthetic images. For the simplified images under consideration, the predicted and empirical ranks showed a promising amount of agreement. One statistic accurately predicted the best and worst background for detection in all of the images. Future work may include explorations of more complicated plume ingredients, background types, and noise structures.« less
Using a Five-Step Procedure for Inferential Statistical Analyses
ERIC Educational Resources Information Center
Kamin, Lawrence F.
2010-01-01
Many statistics texts pose inferential statistical problems in a disjointed way. By using a simple five-step procedure as a template for statistical inference problems, the student can solve problems in an organized fashion. The problem and its solution will thus be a stand-by-itself organic whole and a single unit of thought and effort. The…
Markovic, Gabriela; Schult, Marie-Louise; Bartfai, Aniko; Elg, Mattias
2017-01-31
Progress in early cognitive recovery after acquired brain injury is uneven and unpredictable, and thus the evaluation of rehabilitation is complex. The use of time-series measurements is susceptible to statistical change due to process variation. To evaluate the feasibility of using a time-series method, statistical process control, in early cognitive rehabilitation. Participants were 27 patients with acquired brain injury undergoing interdisciplinary rehabilitation of attention within 4 months post-injury. The outcome measure, the Paced Auditory Serial Addition Test, was analysed using statistical process control. Statistical process control identifies if and when change occurs in the process according to 3 patterns: rapid, steady or stationary performers. The statistical process control method was adjusted, in terms of constructing the baseline and the total number of measurement points, in order to measure a process in change. Statistical process control methodology is feasible for use in early cognitive rehabilitation, since it provides information about change in a process, thus enabling adjustment of the individual treatment response. Together with the results indicating discernible subgroups that respond differently to rehabilitation, statistical process control could be a valid tool in clinical decision-making. This study is a starting-point in understanding the rehabilitation process using a real-time-measurements approach.
ERIC Educational Resources Information Center
Neumann, David L.; Hood, Michelle
2009-01-01
A wiki was used as part of a blended learning approach to promote collaborative learning among students in a first year university statistics class. One group of students analysed a data set and communicated the results by jointly writing a practice report using a wiki. A second group analysed the same data but communicated the results in a…
Relating engagement to outcomes in prevention: the case of a parenting program for couples.
Brown, Louis D; Goslin, Megan C; Feinberg, Mark E
2012-09-01
Analyses of program engagement can provide critical insight into how program involvement leads to outcomes. This study examines the relation between participant engagement and program outcomes in Family Foundations (FF), a universal preventive intervention designed to help couples manage the transition to parenthood by improving coparenting relationship quality. Previous intent-to-treat outcome analyses from a randomized trial indicate FF improves parental adjustment, interparental relationships, and parenting. Analyses for the current study use the same sample, and yield statistically reliable relations between participant engagement and interparental relationships but not parental adjustment or parenting. Discussion considers implications for FF and the difficulties researchers face when examining the relation between engagement and outcomes in preventive interventions.
Relating Engagement to Outcomes in Prevention: The Case of a Parenting Program for Couples
Brown, Louis D.; Goslin, Megan C.; Feinberg, Mark E.
2011-01-01
Analyses of program engagement can provide critical insight into how program involvement leads to outcomes. This study examines the relation between participant engagement and program outcomes in Family Foundations (FF), a universal preventive intervention designed to help couples manage the transition to parenthood by improving coparenting relationship quality. Previous intent-to-treat outcome analyses from a randomized trial indicate FF improves parental adjustment, interparental relationships, and parenting. Analyses for the current study use the same sample, and yield statistically reliable relations between participant engagement and interparental relationships but not parental adjustment or parenting. Discussion considers implications for FF and the difficulities researchers face when examining the relation between engagement and outcomes in preventive interventions. PMID:21826536
Chaisinanunkul, Napasri; Adeoye, Opeolu; Lewis, Roger J; Grotta, James C; Broderick, Joseph; Jovin, Tudor G; Nogueira, Raul G; Elm, Jordan J; Graves, Todd; Berry, Scott; Lees, Kennedy R; Barreto, Andrew D; Saver, Jeffrey L
2015-08-01
Although the modified Rankin Scale (mRS) is the most commonly used primary end point in acute stroke trials, its power is limited when analyzed in dichotomized fashion and its indication of effect size challenging to interpret when analyzed ordinally. Weighting the 7 Rankin levels by utilities may improve scale interpretability while preserving statistical power. A utility-weighted mRS (UW-mRS) was derived by averaging values from time-tradeoff (patient centered) and person-tradeoff (clinician centered) studies. The UW-mRS, standard ordinal mRS, and dichotomized mRS were applied to 11 trials or meta-analyses of acute stroke treatments, including lytic, endovascular reperfusion, blood pressure moderation, and hemicraniectomy interventions. Utility values were 1.0 for mRS level 0; 0.91 for mRS level 1; 0.76 for mRS level 2; 0.65 for mRS level 3; 0.33 for mRS level 4; 0 for mRS level 5; and 0 for mRS level 6. For trials with unidirectional treatment effects, the UW-mRS paralleled the ordinal mRS and outperformed dichotomous mRS analyses. Both the UW-mRS and the ordinal mRS were statistically significant in 6 of 8 unidirectional effect trials, whereas dichotomous analyses were statistically significant in 2 to 4 of 8. In bidirectional effect trials, both the UW-mRS and ordinal tests captured the divergent treatment effects by showing neutral results, whereas some dichotomized analyses showed positive results. Mean utility differences in trials with statistically significant positive results ranged from 0.026 to 0.249. A UW-mRS performs similar to the standard ordinal mRS in detecting treatment effects in actual stroke trials and ensures the quantitative outcome is a valid reflection of patient-centered benefits. © 2015 American Heart Association, Inc.
McKinley, Christopher J; Limbu, Yam; Jayachandran, C N
2017-04-01
In two separate investigations, we examined the persuasive effectiveness of statistical versus exemplar appeals on Indian adults' smoking cessation and mammography screening intentions. To more comprehensively address persuasion processes, we explored whether message response and perceived message effectiveness functioned as antecedents to persuasive effects. Results showed that statistical appeals led to higher levels of health intentions than exemplar appeals. In addition, findings from both studies indicated that statistical appeals stimulated more attention and were perceived as more effective than anecdotal accounts. Among male smokers, statistical appeals also generated greater cognitive processing than exemplar appeals. Subsequent mediation analyses revealed that message response and perceived message effectiveness fully carried the influence of appeal format on health intentions. Given these findings, future public health initiatives conducted among similar populations should design messages that include substantive factual information while ensuring that this content is perceived as credible and valuable.
Emotional Intelligence Profiles and Learning Strategies in Secondary School Students
ERIC Educational Resources Information Center
Inglés, Cándido J.; Martínez-Monteagudo, María C.; Pérez Fuentes, Maria C.; García-Fernández, José M.; Molero, María del Mar; Suriá-Martinez, Raquel; Gázquez, José J.
2017-01-01
The aim of this study was to analyse the relationship among emotional intelligence (EI) and learning strategies, identifying different emotional intelligence profiles and determining possible statistically significant differences in learning strategies through the identified profiles. Thousand and seventy-one Spaniards secondary school students…
Nitrogen Dioxide Exposure and Airway Responsiveness in Individuals with Asthma
Controlled human exposure studies evaluating the effect of inhaled NO2 on the inherent responsiveness of the airways to challenge by bronchoconstricting agents have had mixed results. In general, existing meta-analyses show statistically significant effects of NO2 on the airway r...
Critical Thinking in the Business Classroom
ERIC Educational Resources Information Center
Reid, Joanne R.; Anderson, Phyllis R.
2012-01-01
A minicourse in critical thinking was implemented to improve student outcomes in two sessions of a senior-level business course at a Midwestern university. Statistical analyses of two quantitative assessments revealed significant improvements in critical thinking skills. Improvements in student outcomes in case studies and computerized business…
Multilingualism, Empathy and Multicompetence
ERIC Educational Resources Information Center
Dewaele, Jean-Marc; Wei, Li
2012-01-01
The present study investigates the link between multilingualism and the personality trait of cognitive empathy among 2158 mono- and multilinguals. Data were collected through an online questionnaire. Statistical analyses revealed that the knowledge of more languages was not linked to cognitive empathy. Bilingual upbringing and the experience of…
ERIC Educational Resources Information Center
Ellis, Thomas I.
1985-01-01
After a brief introduction identifying current issues and trends in research on class size, this brochure reviews five recent studies bearing on the relationship of class size to educational effectiveness. Part 1 is a review of two interrelated and highly controversial "meta-analyses" or statistical integrations of research findings on…
DOT National Transportation Integrated Search
1983-01-01
This study attempted to establish and analyze relationships between forms of deterioration or distress that reduce the level of service provided by a highway pavement and the cost of correcting them. Using statistical computer analyses of 30 highway ...
Nieuwenhuys, Angela; Papageorgiou, Eirini; Desloovere, Kaat; Molenaers, Guy; De Laet, Tinne
2017-01-01
Experts recently identified 49 joint motion patterns in children with cerebral palsy during a Delphi consensus study. Pattern definitions were therefore the result of subjective expert opinion. The present study aims to provide objective, quantitative data supporting the identification of these consensus-based patterns. To do so, statistical parametric mapping was used to compare the mean kinematic waveforms of 154 trials of typically developing children (n = 56) to the mean kinematic waveforms of 1719 trials of children with cerebral palsy (n = 356), which were classified following the classification rules of the Delphi study. Three hypotheses stated that: (a) joint motion patterns with 'no or minor gait deviations' (n = 11 patterns) do not differ significantly from the gait pattern of typically developing children; (b) all other pathological joint motion patterns (n = 38 patterns) differ from typically developing gait and the locations of difference within the gait cycle, highlighted by statistical parametric mapping, concur with the consensus-based classification rules. (c) all joint motion patterns at the level of each joint (n = 49 patterns) differ from each other during at least one phase of the gait cycle. Results showed that: (a) ten patterns with 'no or minor gait deviations' differed somewhat unexpectedly from typically developing gait, but these differences were generally small (≤3°); (b) all other joint motion patterns (n = 38) differed from typically developing gait and the significant locations within the gait cycle that were indicated by the statistical analyses, coincided well with the classification rules; (c) joint motion patterns at the level of each joint significantly differed from each other, apart from two sagittal plane pelvic patterns. In addition to these results, for several joints, statistical analyses indicated other significant areas during the gait cycle that were not included in the pattern definitions of the consensus study. Based on these findings, suggestions to improve pattern definitions were made.
Papageorgiou, Eirini; Desloovere, Kaat; Molenaers, Guy; De Laet, Tinne
2017-01-01
Experts recently identified 49 joint motion patterns in children with cerebral palsy during a Delphi consensus study. Pattern definitions were therefore the result of subjective expert opinion. The present study aims to provide objective, quantitative data supporting the identification of these consensus-based patterns. To do so, statistical parametric mapping was used to compare the mean kinematic waveforms of 154 trials of typically developing children (n = 56) to the mean kinematic waveforms of 1719 trials of children with cerebral palsy (n = 356), which were classified following the classification rules of the Delphi study. Three hypotheses stated that: (a) joint motion patterns with ‘no or minor gait deviations’ (n = 11 patterns) do not differ significantly from the gait pattern of typically developing children; (b) all other pathological joint motion patterns (n = 38 patterns) differ from typically developing gait and the locations of difference within the gait cycle, highlighted by statistical parametric mapping, concur with the consensus-based classification rules. (c) all joint motion patterns at the level of each joint (n = 49 patterns) differ from each other during at least one phase of the gait cycle. Results showed that: (a) ten patterns with ‘no or minor gait deviations’ differed somewhat unexpectedly from typically developing gait, but these differences were generally small (≤3°); (b) all other joint motion patterns (n = 38) differed from typically developing gait and the significant locations within the gait cycle that were indicated by the statistical analyses, coincided well with the classification rules; (c) joint motion patterns at the level of each joint significantly differed from each other, apart from two sagittal plane pelvic patterns. In addition to these results, for several joints, statistical analyses indicated other significant areas during the gait cycle that were not included in the pattern definitions of the consensus study. Based on these findings, suggestions to improve pattern definitions were made. PMID:28081229
Fruit and vegetable intake and risk of breast cancer by hormone receptor status.
Jung, Seungyoun; Spiegelman, Donna; Baglietto, Laura; Bernstein, Leslie; Boggs, Deborah A; van den Brandt, Piet A; Buring, Julie E; Cerhan, James R; Gaudet, Mia M; Giles, Graham G; Goodman, Gary; Hakansson, Niclas; Hankinson, Susan E; Helzlsouer, Kathy; Horn-Ross, Pamela L; Inoue, Manami; Krogh, Vittorio; Lof, Marie; McCullough, Marjorie L; Miller, Anthony B; Neuhouser, Marian L; Palmer, Julie R; Park, Yikyung; Robien, Kim; Rohan, Thomas E; Scarmo, Stephanie; Schairer, Catherine; Schouten, Leo J; Shikany, James M; Sieri, Sabina; Tsugane, Schoichiro; Visvanathan, Kala; Weiderpass, Elisabete; Willett, Walter C; Wolk, Alicja; Zeleniuch-Jacquotte, Anne; Zhang, Shumin M; Zhang, Xuehong; Ziegler, Regina G; Smith-Warner, Stephanie A
2013-02-06
Estrogen receptor-negative (ER(-)) breast cancer has few known or modifiable risk factors. Because ER(-) tumors account for only 15% to 20% of breast cancers, large pooled analyses are necessary to evaluate precisely the suspected inverse association between fruit and vegetable intake and risk of ER(-) breast cancer. Among 993 466 women followed for 11 to 20 years in 20 cohort studies, we documented 19 869 estrogen receptor positive (ER(+)) and 4821 ER(-) breast cancers. We calculated study-specific multivariable relative risks (RRs) and 95% confidence intervals (CIs) using Cox proportional hazards regression analyses and then combined them using a random-effects model. All statistical tests were two-sided. Total fruit and vegetable intake was statistically significantly inversely associated with risk of ER(-) breast cancer but not with risk of breast cancer overall or of ER(+) tumors. The inverse association for ER(-) tumors was observed primarily for vegetable consumption. The pooled relative risks comparing the highest vs lowest quintile of total vegetable consumption were 0.82 (95% CI = 0.74 to 0.90) for ER(-) breast cancer and 1.04 (95% CI = 0.97 to 1.11) for ER(+) breast cancer (P (common-effects) by ER status < .001). Total fruit consumption was non-statistically significantly associated with risk of ER(-) breast cancer (pooled multivariable RR comparing the highest vs lowest quintile = 0.94, 95% CI = 0.85 to 1.04). We observed no association between total fruit and vegetable intake and risk of overall breast cancer. However, vegetable consumption was inversely associated with risk of ER(-) breast cancer in our large pooled analyses.
Lederer, David J; Bradford, Williamson Z; Fagan, Elizabeth A; Glaspole, Ian; Glassberg, Marilyn K; Glasscock, Kenneth F; Kardatzke, David; King, Talmadge E; Lancaster, Lisa H; Nathan, Steven D; Pereira, Carlos A; Sahn, Steven A; Swigris, Jeffrey J; Noble, Paul W
2015-07-01
FVC outcomes in clinical trials on idiopathic pulmonary fibrosis (IPF) can be substantially influenced by the analytic methodology and the handling of missing data. We conducted a series of sensitivity analyses to assess the robustness of the statistical finding and the stability of the estimate of the magnitude of treatment effect on the primary end point of FVC change in a phase 3 trial evaluating pirfenidone in adults with IPF. Source data included all 555 study participants randomized to treatment with pirfenidone or placebo in the Assessment of Pirfenidone to Confirm Efficacy and Safety in Idiopathic Pulmonary Fibrosis (ASCEND) study. Sensitivity analyses were conducted to assess whether alternative statistical tests and methods for handling missing data influenced the observed magnitude of treatment effect on the primary end point of change from baseline to week 52 in FVC. The distribution of FVC change at week 52 was systematically different between the two treatment groups and favored pirfenidone in each analysis. The method used to impute missing data due to death had a marked effect on the magnitude of change in FVC in both treatment groups; however, the magnitude of treatment benefit was generally consistent on a relative basis, with an approximate 50% reduction in FVC decline observed in the pirfenidone group in each analysis. Our results confirm the robustness of the statistical finding on the primary end point of change in FVC in the ASCEND trial and corroborate the estimated magnitude of the pirfenidone treatment effect in patients with IPF. ClinicalTrials.gov; No.: NCT01366209; URL: www.clinicaltrials.gov.
Systematic review of wireless phone use and brain cancer and other head tumors.
Repacholi, Michael H; Lerchl, Alexander; Röösli, Martin; Sienkiewicz, Zenon; Auvinen, Anssi; Breckenkamp, Jürgen; d'Inzeo, Guglielmo; Elliott, Paul; Frei, Patrizia; Heinrich, Sabine; Lagroye, Isabelle; Lahkola, Anna; McCormick, David L; Thomas, Silke; Vecchia, Paolo
2012-04-01
We conducted a systematic review of scientific studies to evaluate whether the use of wireless phones is linked to an increased incidence of the brain cancer glioma or other tumors of the head (meningioma, acoustic neuroma, and parotid gland), originating in the areas of the head that most absorb radiofrequency (RF) energy from wireless phones. Epidemiology and in vivo studies were evaluated according to an agreed protocol; quality criteria were used to evaluate the studies for narrative synthesis but not for meta-analyses or pooling of results. The epidemiology study results were heterogeneous, with sparse data on long-term use (≥ 10 years). Meta-analyses of the epidemiology studies showed no statistically significant increase in risk (defined as P < 0.05) for adult brain cancer or other head tumors from wireless phone use. Analyses of the in vivo oncogenicity, tumor promotion, and genotoxicity studies also showed no statistically significant relationship between exposure to RF fields and genotoxic damage to brain cells, or the incidence of brain cancers or other tumors of the head. Assessment of the review results using the Hill criteria did not support a causal relationship between wireless phone use and the incidence of adult cancers in the areas of the head that most absorb RF energy from the use of wireless phones. There are insufficient data to make any determinations about longer-term use (≥ 10 years). © 2011 Wiley Periodicals, Inc.
Mindful attention and awareness: relationships with psychopathology and emotion regulation.
Gregório, Sónia; Pinto-Gouveia, José
2013-01-01
The growing interest in mindfulness from the scientific community has originated several self-report measures of this psychological construct. The Mindful Attention and Awareness Scale (MAAS) is a self-report measure of mindfulness at a trait-level. This paper aims at exploring MAAS psychometric characteristics and validating it for the Portuguese population. The first two studies replicate some of the original author's statistical procedures in two different samples from the Portuguese general community population, in particular confirmatory factor analyses. Results from both analyses confirmed the scale single-factor structure and indicated a very good reliability. Moreover, cross-validation statistics showed that this single-factor structure is valid for different respondents from the general community population. In the third study the Portuguese version of the MAAS was found to have good convergent and discriminant validities. Overall the findings support the psychometric validity of the Portuguese version of MAAS and suggest this is a reliable self-report measure of trait-mindfulness, a central construct in Clinical Psychology research and intervention fields.
Parasites as valuable stock markers for fisheries in Australasia, East Asia and the Pacific Islands.
Lester, R J G; Moore, B R
2015-01-01
Over 30 studies in Australasia, East Asia and the Pacific Islands region have collected and analysed parasite data to determine the ranges of individual fish, many leading to conclusions about stock delineation. Parasites used as biological tags have included both those known to have long residence times in the fish and those thought to be relatively transient. In many cases the parasitological conclusions have been supported by other methods especially analysis of the chemical constituents of otoliths, and to a lesser extent, genetic data. In analysing parasite data, authors have applied multiple different statistical methodologies, including summary statistics, and univariate and multivariate approaches. Recently, a growing number of researchers have found non-parametric methods, such as analysis of similarities and cluster analysis, to be valuable. Future studies into the residence times, life cycles and geographical distributions of parasites together with more robust analytical methods will yield much important information to clarify stock structures in the area.
NASA Astrophysics Data System (ADS)
Pignalosa, Antonio; Di Crescenzo, Giuseppe; Marino, Ermanno; Terracciano, Rosario; Santo, Antonio
2015-04-01
The work here presented concerns a case study in which a complete multidisciplinary workflow has been applied for an extensive assessment of the rockslide susceptibility and hazard in a common scenario such as a vertical and fractured rocky cliffs. The studied area is located in a high-relief zone in Southern Italy (Sacco, Salerno, Campania), characterized by wide vertical rocky cliffs formed by tectonized thick successions of shallow-water limestones. The study concerned the following phases: a) topographic surveying integrating of 3d laser scanning, photogrammetry and GNSS; b) gelogical surveying, characterization of single instabilities and geomecanichal surveying, conducted by geologists rock climbers; c) processing of 3d data and reconstruction of high resolution geometrical models; d) structural and geomechanical analyses; e) data filing in a GIS-based spatial database; f) geo-statistical and spatial analyses and mapping of the whole set of data; g) 3D rockfall analysis; The main goals of the study have been a) to set-up an investigation method to achieve a complete and thorough characterization of the slope stability conditions and b) to provide a detailed base for an accurate definition of the reinforcement and mitigation systems. For this purposes the most up-to-date methods of field surveying, remote sensing, 3d modelling and geospatial data analysis have been integrated in a systematic workflow, accounting of the economic sustainability of the whole project. A novel integrated approach have been applied both fusing deterministic and statistical surveying methods. This approach enabled to deal with the wide extension of the studied area (near to 200.000 m2), without compromising an high accuracy of the results. The deterministic phase, based on a field characterization of single instabilities and their further analyses on 3d models, has been applied for delineating the peculiarity of each single feature. The statistical approach, based on geostructural field mapping and on punctual geomechanical data from scan-line surveying, allowed the rock mass partitioning in homogeneous geomechanical sectors and data interpolation through bounded geostatistical analyses on 3d models. All data, resulting from both approaches, have been referenced and filed in a single spatial database and considered in global geo-statistical analyses for deriving a fully modelled and comprehensive evaluation of the rockslide susceptibility. The described workflow yielded the following innovative results: a) a detailed census of single potential instabilities, through a spatial database recording the geometrical, geological and mechanical features, along with the expected failure modes; b) an high resolution characterization of the whole slope rockslide susceptibility, based on the partitioning of the area according to the stability and mechanical conditions which can be directly related to specific hazard mitigation systems; c) the exact extension of the area exposed to the rockslide hazard, along with the dynamic parameters of expected phenomena; d) an intervention design for hazard mitigation.
Reliable mortality statistics for Turkey: Are we there yet?
Özdemir, Raziye; Rao, Chalapati; Öcek, Zeliha; Dinç Horasan, Gönül
2015-06-10
The Turkish government has implemented several reforms to improve the Turkish Statistical Institute Death Reporting System (TURKSTAT-DRS) since 2009. However, there has been no assessment to evaluate the impact of these reforms on causes of death statistics. This study attempted to analyse the impact of these reforms on the TURKSTAT-DRS for Turkey, and in the case of Izmir, one of the most developed provinces in Turkey. The evaluation framework comprised three main components each with specific criteria. Firstly, data from TURKSTAT for Turkey and Izmir for the periods 2001-2008 and 2009-2013 were assessed in terms of the following dimensions that represent quality of mortality statistics (a. completeness of death registration, b. trends in proportions of deaths with ill-defined causes). Secondly, the quality of information recorded on individual death certificates from Izmir in 2010 was analysed for a. missing information, b. timeliness of death notifications and c. characteristics of deaths with ill-defined causes. Finally, TURKSTAT data were analysed to estimate life tables and summary mortality indicators for Turkey and Izmir, as well as the leading causes-of-death in Turkey in 2013. Registration of adult deaths in Izmir as well as at the national level for Turkey has considerably improved since the introduction of reforms in 2009, along with marked decline in the proportions of deaths assigned ill-defined causes. Death certificates from Izmir indicated significant gaps in recorded information for demographic as well as epidemiological variables, particularly for infant deaths, and in the detailed recording of causes of death. Life expectancy at birth estimated from local data is 3-4 years higher than similar estimates for Turkey from international studies, and this requires further investigation and confirmation. The TURKSTAT-DRS is now an improved source of mortality and cause of death statistics for Turkey. The reliability and validity of TURKSTAT data needs to be established through a detailed research program to evaluate completeness of death registration and validity of registered causes of death. Similar evaluation and data analysis of mortality indicators is required at regular intervals at national and sub-national level, to increase confidence in their utility as primary data for epidemiology and health policy.
Wallach, Joshua D; Sullivan, Patrick G; Trepanowski, John F; Sainani, Kristin L; Steyerberg, Ewout W; Ioannidis, John P A
2017-04-01
Many published randomized clinical trials (RCTs) make claims for subgroup differences. To evaluate how often subgroup claims reported in the abstracts of RCTs are actually supported by statistical evidence (P < .05 from an interaction test) and corroborated by subsequent RCTs and meta-analyses. This meta-epidemiological survey examines data sets of trials with at least 1 subgroup claim, including Subgroup Analysis of Trials Is Rarely Easy (SATIRE) articles and Discontinuation of Randomized Trials (DISCO) articles. We used Scopus (updated July 2016) to search for English-language articles citing each of the eligible index articles with at least 1 subgroup finding in the abstract. Articles with a subgroup claim in the abstract with or without evidence of statistical heterogeneity (P < .05 from an interaction test) in the text and articles attempting to corroborate the subgroup findings. Study characteristics of trials with at least 1 subgroup claim in the abstract were recorded. Two reviewers extracted the data necessary to calculate subgroup-level effect sizes, standard errors, and the P values for interaction. For individual RCTs and meta-analyses that attempted to corroborate the subgroup findings from the index articles, trial characteristics were extracted. Cochran Q test was used to reevaluate heterogeneity with the data from all available trials. The number of subgroup claims in the abstracts of RCTs, the number of subgroup claims in the abstracts of RCTs with statistical support (subgroup findings), and the number of subgroup findings corroborated by subsequent RCTs and meta-analyses. Sixty-four eligible RCTs made a total of 117 subgroup claims in their abstracts. Of these 117 claims, only 46 (39.3%) in 33 articles had evidence of statistically significant heterogeneity from a test for interaction. In addition, out of these 46 subgroup findings, only 16 (34.8%) ensured balance between randomization groups within the subgroups (eg, through stratified randomization), 13 (28.3%) entailed a prespecified subgroup analysis, and 1 (2.2%) was adjusted for multiple testing. Only 5 (10.9%) of the 46 subgroup findings had at least 1 subsequent pure corroboration attempt by a meta-analysis or an RCT. In all 5 cases, the corroboration attempts found no evidence of a statistically significant subgroup effect. In addition, all effect sizes from meta-analyses were attenuated toward the null. A minority of subgroup claims made in the abstracts of RCTs are supported by their own data (ie, a significant interaction effect). For those that have statistical support (P < .05 from an interaction test), most fail to meet other best practices for subgroup tests, including prespecification, stratified randomization, and adjustment for multiple testing. Attempts to corroborate statistically significant subgroup differences are rare; when done, the initially observed subgroup differences are not reproduced.
Statistical modelling for recurrent events: an application to sports injuries
Ullah, Shahid; Gabbett, Tim J; Finch, Caroline F
2014-01-01
Background Injuries are often recurrent, with subsequent injuries influenced by previous occurrences and hence correlation between events needs to be taken into account when analysing such data. Objective This paper compares five different survival models (Cox proportional hazards (CoxPH) model and the following generalisations to recurrent event data: Andersen-Gill (A-G), frailty, Wei-Lin-Weissfeld total time (WLW-TT) marginal, Prentice-Williams-Peterson gap time (PWP-GT) conditional models) for the analysis of recurrent injury data. Methods Empirical evaluation and comparison of different models were performed using model selection criteria and goodness-of-fit statistics. Simulation studies assessed the size and power of each model fit. Results The modelling approach is demonstrated through direct application to Australian National Rugby League recurrent injury data collected over the 2008 playing season. Of the 35 players analysed, 14 (40%) players had more than 1 injury and 47 contact injuries were sustained over 29 matches. The CoxPH model provided the poorest fit to the recurrent sports injury data. The fit was improved with the A-G and frailty models, compared to WLW-TT and PWP-GT models. Conclusions Despite little difference in model fit between the A-G and frailty models, in the interest of fewer statistical assumptions it is recommended that, where relevant, future studies involving modelling of recurrent sports injury data use the frailty model in preference to the CoxPH model or its other generalisations. The paper provides a rationale for future statistical modelling approaches for recurrent sports injury. PMID:22872683
Statistical universals reveal the structures and functions of human music.
Savage, Patrick E; Brown, Steven; Sakai, Emi; Currie, Thomas E
2015-07-21
Music has been called "the universal language of mankind." Although contemporary theories of music evolution often invoke various musical universals, the existence of such universals has been disputed for decades and has never been empirically demonstrated. Here we combine a music-classification scheme with statistical analyses, including phylogenetic comparative methods, to examine a well-sampled global set of 304 music recordings. Our analyses reveal no absolute universals but strong support for many statistical universals that are consistent across all nine geographic regions sampled. These universals include 18 musical features that are common individually as well as a network of 10 features that are commonly associated with one another. They span not only features related to pitch and rhythm that are often cited as putative universals but also rarely cited domains including performance style and social context. These cross-cultural structural regularities of human music may relate to roles in facilitating group coordination and cohesion, as exemplified by the universal tendency to sing, play percussion instruments, and dance to simple, repetitive music in groups. Our findings highlight the need for scientists studying music evolution to expand the range of musical cultures and musical features under consideration. The statistical universals we identified represent important candidates for future investigation.
Statistical universals reveal the structures and functions of human music
Savage, Patrick E.; Brown, Steven; Sakai, Emi; Currie, Thomas E.
2015-01-01
Music has been called “the universal language of mankind.” Although contemporary theories of music evolution often invoke various musical universals, the existence of such universals has been disputed for decades and has never been empirically demonstrated. Here we combine a music-classification scheme with statistical analyses, including phylogenetic comparative methods, to examine a well-sampled global set of 304 music recordings. Our analyses reveal no absolute universals but strong support for many statistical universals that are consistent across all nine geographic regions sampled. These universals include 18 musical features that are common individually as well as a network of 10 features that are commonly associated with one another. They span not only features related to pitch and rhythm that are often cited as putative universals but also rarely cited domains including performance style and social context. These cross-cultural structural regularities of human music may relate to roles in facilitating group coordination and cohesion, as exemplified by the universal tendency to sing, play percussion instruments, and dance to simple, repetitive music in groups. Our findings highlight the need for scientists studying music evolution to expand the range of musical cultures and musical features under consideration. The statistical universals we identified represent important candidates for future investigation. PMID:26124105
Ge, Long; Tian, Jin-hui; Li, Xiu-xia; Song, Fujian; Li, Lun; Zhang, Jun; Li, Ge; Pei, Gai-qin; Qiu, Xia; Yang, Ke-hu
2016-01-01
Because of the methodological complexity of network meta-analyses (NMAs), NMAs may be more vulnerable to methodological risks than conventional pair-wise meta-analysis. Our study aims to investigate epidemiology characteristics, conduction of literature search, methodological quality and reporting of statistical analysis process in the field of cancer based on PRISMA extension statement and modified AMSTAR checklist. We identified and included 102 NMAs in the field of cancer. 61 NMAs were conducted using a Bayesian framework. Of them, more than half of NMAs did not report assessment of convergence (60.66%). Inconsistency was assessed in 27.87% of NMAs. Assessment of heterogeneity in traditional meta-analyses was more common (42.62%) than in NMAs (6.56%). Most of NMAs did not report assessment of similarity (86.89%) and did not used GRADE tool to assess quality of evidence (95.08%). 43 NMAs were adjusted indirect comparisons, the methods used were described in 53.49% NMAs. Only 4.65% NMAs described the details of handling of multi group trials and 6.98% described the methods of similarity assessment. The median total AMSTAR-score was 8.00 (IQR: 6.00–8.25). Methodological quality and reporting of statistical analysis did not substantially differ by selected general characteristics. Overall, the quality of NMAs in the field of cancer was generally acceptable. PMID:27848997
Dynamic properties of small-scale solar wind plasma fluctuations.
Riazantseva, M O; Budaev, V P; Zelenyi, L M; Zastenker, G N; Pavlos, G P; Safrankova, J; Nemecek, Z; Prech, L; Nemec, F
2015-05-13
The paper presents the latest results of the studies of small-scale fluctuations in a turbulent flow of solar wind (SW) using measurements with extremely high temporal resolution (up to 0.03 s) of the bright monitor of SW (BMSW) plasma spectrometer operating on astrophysical SPECTR-R spacecraft at distances up to 350,000 km from the Earth. The spectra of SW ion flux fluctuations in the range of scales between 0.03 and 100 s are systematically analysed. The difference of slopes in low- and high-frequency parts of spectra and the frequency of the break point between these two characteristic slopes was analysed for different conditions in the SW. The statistical properties of the SW ion flux fluctuations were thoroughly analysed on scales less than 10 s. A high level of intermittency is demonstrated. The extended self-similarity of SW ion flux turbulent flow is constantly observed. The approximation of non-Gaussian probability distribution function of ion flux fluctuations by the Tsallis statistics shows the non-extensive character of SW fluctuations. Statistical characteristics of ion flux fluctuations are compared with the predictions of a log-Poisson model. The log-Poisson parametrization of the structure function scaling has shown that well-defined filament-like plasma structures are, as a rule, observed in the turbulent SW flows. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
Distribution of water quality parameters in Dhemaji district, Assam (India).
Buragohain, Mridul; Bhuyan, Bhabajit; Sarma, H P
2010-07-01
The primary objective of this study is to present a statistically significant water quality database of Dhemaji district, Assam (India) with special reference to pH, fluoride, nitrate, arsenic, iron, sodium and potassium. 25 water samples collected from different locations of five development blocks in Dhemaji district have been studied separately. The implications presented are based on statistical analyses of the raw data. Normal distribution statistics and reliability analysis (correlation and covariance matrix) have been employed to find out the distribution pattern, localisation of data, and other related information. Statistical observations show that all the parameters under investigation exhibit non uniform distribution with a long asymmetric tail either on the right or left side of the median. The width of the third quartile was consistently found to be more than the second quartile for each parameter. Differences among mean, mode and median, significant skewness and kurtosis value indicate that the distribution of various water quality parameters in the study area is widely off normal. Thus, the intrinsic water quality is not encouraging due to unsymmetrical distribution of various water quality parameters in the study area.
An Adaptive Association Test for Multiple Phenotypes with GWAS Summary Statistics.
Kim, Junghi; Bai, Yun; Pan, Wei
2015-12-01
We study the problem of testing for single marker-multiple phenotype associations based on genome-wide association study (GWAS) summary statistics without access to individual-level genotype and phenotype data. For most published GWASs, because obtaining summary data is substantially easier than accessing individual-level phenotype and genotype data, while often multiple correlated traits have been collected, the problem studied here has become increasingly important. We propose a powerful adaptive test and compare its performance with some existing tests. We illustrate its applications to analyses of a meta-analyzed GWAS dataset with three blood lipid traits and another with sex-stratified anthropometric traits, and further demonstrate its potential power gain over some existing methods through realistic simulation studies. We start from the situation with only one set of (possibly meta-analyzed) genome-wide summary statistics, then extend the method to meta-analysis of multiple sets of genome-wide summary statistics, each from one GWAS. We expect the proposed test to be useful in practice as more powerful than or complementary to existing methods. © 2015 WILEY PERIODICALS, INC.
Recent evaluations of crack-opening-area in circumferentially cracked pipes
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rahman, S.; Brust, F.; Ghadiali, N.
1997-04-01
Leak-before-break (LBB) analyses for circumferentially cracked pipes are currently being conducted in the nuclear industry to justify elimination of pipe whip restraints and jet shields which are present because of the expected dynamic effects from pipe rupture. The application of the LBB methodology frequently requires calculation of leak rates. The leak rates depend on the crack-opening area of the through-wall crack in the pipe. In addition to LBB analyses which assume a hypothetical flaw size, there is also interest in the integrity of actual leaking cracks corresponding to current leakage detection requirements in NRC Regulatory Guide 1.45, or for assessingmore » temporary repair of Class 2 and 3 pipes that have leaks as are being evaluated in ASME Section XI. The objectives of this study were to review, evaluate, and refine current predictive models for performing crack-opening-area analyses of circumferentially cracked pipes. The results from twenty-five full-scale pipe fracture experiments, conducted in the Degraded Piping Program, the International Piping Integrity Research Group Program, and the Short Cracks in Piping and Piping Welds Program, were used to verify the analytical models. Standard statistical analyses were performed to assess used to verify the analytical models. Standard statistical analyses were performed to assess quantitatively the accuracy of the predictive models. The evaluation also involved finite element analyses for determining the crack-opening profile often needed to perform leak-rate calculations.« less
Acconcia, M C; Caretta, Q; Romeo, F; Borzi, M; Perrone, M A; Sergi, D; Chiarotti, F; Calabrese, C M; Sili Scavalli, A; Gaudio, C
2018-04-01
Intra-aortic balloon pump (IABP) is the device most commonly investigated in patients with cardiogenic shock (CS) complicating acute myocardial infarction (AMI). Recently meta-analyses on this topic showed opposite results: some complied with the actual guideline recommendations, while others did not, due to the presence of bias. We investigated the reasons for the discrepancy among meta-analyses and strategies employed to avoid the potential source of bias. Scientific databases were searched for meta-analyses of IABP support in AMI complicated by CS. The presence of clinical diversity, methodological diversity and statistical heterogeneity were analyzed. When we found clinical or methodological diversity, we reanalyzed the data by comparing the patients selected for homogeneous groups. When the fixed effect model was employed despite the presence of statistical heterogeneity, the meta-analysis was repeated adopting the random effect model, with the same estimator used in the original meta-analysis. Twelve meta-analysis were selected. Six meta-analyses of randomized controlled trials (RCTs) were inconclusive because underpowered to detect the IABP effect. Five included RCTs and observational studies (Obs) and one only Obs. Some meta-analyses on RCTs and Obs had biased results due to presence of clinical and/or methodological diversity. The reanalysis of data reallocated for homogeneous groups was no more in contrast with guidelines recommendations. Meta-analyses performed without controlling for clinical and/or methodological diversity, represent a confounding message against a good clinical practice. The reanalysis of data demonstrates the validity of the current guidelines recommendations in addressing clinical decision making in providing IABP support in AMI complicated by CS.
NASA Astrophysics Data System (ADS)
ten Veldhuis, Marie-Claire; Schleiss, Marc
2017-04-01
In this study, we introduced an alternative approach for analysis of hydrological flow time series, using an adaptive sampling framework based on inter-amount times (IATs). The main difference with conventional flow time series is the rate at which low and high flows are sampled: the unit of analysis for IATs is a fixed flow amount, instead of a fixed time window. We analysed statistical distributions of flows and IATs across a wide range of sampling scales to investigate sensitivity of statistical properties such as quantiles, variance, skewness, scaling parameters and flashiness indicators to the sampling scale. We did this based on streamflow time series for 17 (semi)urbanised basins in North Carolina, US, ranging from 13 km2 to 238 km2 in size. Results showed that adaptive sampling of flow time series based on inter-amounts leads to a more balanced representation of low flow and peak flow values in the statistical distribution. While conventional sampling gives a lot of weight to low flows, as these are most ubiquitous in flow time series, IAT sampling gives relatively more weight to high flow values, when given flow amounts are accumulated in shorter time. As a consequence, IAT sampling gives more information about the tail of the distribution associated with high flows, while conventional sampling gives relatively more information about low flow periods. We will present results of statistical analyses across a range of subdaily to seasonal scales and will highlight some interesting insights that can be derived from IAT statistics with respect to basin flashiness and impact urbanisation on hydrological response.
2013-01-01
Background The theoretical basis of genome-wide association studies (GWAS) is statistical inference of linkage disequilibrium (LD) between any polymorphic marker and a putative disease locus. Most methods widely implemented for such analyses are vulnerable to several key demographic factors and deliver a poor statistical power for detecting genuine associations and also a high false positive rate. Here, we present a likelihood-based statistical approach that accounts properly for non-random nature of case–control samples in regard of genotypic distribution at the loci in populations under study and confers flexibility to test for genetic association in presence of different confounding factors such as population structure, non-randomness of samples etc. Results We implemented this novel method together with several popular methods in the literature of GWAS, to re-analyze recently published Parkinson’s disease (PD) case–control samples. The real data analysis and computer simulation show that the new method confers not only significantly improved statistical power for detecting the associations but also robustness to the difficulties stemmed from non-randomly sampling and genetic structures when compared to its rivals. In particular, the new method detected 44 significant SNPs within 25 chromosomal regions of size < 1 Mb but only 6 SNPs in two of these regions were previously detected by the trend test based methods. It discovered two SNPs located 1.18 Mb and 0.18 Mb from the PD candidates, FGF20 and PARK8, without invoking false positive risk. Conclusions We developed a novel likelihood-based method which provides adequate estimation of LD and other population model parameters by using case and control samples, the ease in integration of these samples from multiple genetically divergent populations and thus confers statistically robust and powerful analyses of GWAS. On basis of simulation studies and analysis of real datasets, we demonstrated significant improvement of the new method over the non-parametric trend test, which is the most popularly implemented in the literature of GWAS. PMID:23394771
Conceptual and statistical problems associated with the use of diversity indices in ecology.
Barrantes, Gilbert; Sandoval, Luis
2009-09-01
Diversity indices, particularly the Shannon-Wiener index, have extensively been used in analyzing patterns of diversity at different geographic and ecological scales. These indices have serious conceptual and statistical problems which make comparisons of species richness or species abundances across communities nearly impossible. There is often no a single statistical method that retains all information needed to answer even a simple question. However, multivariate analyses could be used instead of diversity indices, such as cluster analyses or multiple regressions. More complex multivariate analyses, such as Canonical Correspondence Analysis, provide very valuable information on environmental variables associated to the presence and abundance of the species in a community. In addition, particular hypotheses associated to changes in species richness across localities, or change in abundance of one, or a group of species can be tested using univariate, bivariate, and/or rarefaction statistical tests. The rarefaction method has proved to be robust to standardize all samples to a common size. Even the simplest method as reporting the number of species per taxonomic category possibly provides more information than a diversity index value.
Lightfoot, Emma; O’Connell, Tamsin C.
2016-01-01
Oxygen isotope analysis of archaeological skeletal remains is an increasingly popular tool to study past human migrations. It is based on the assumption that human body chemistry preserves the δ18O of precipitation in such a way as to be a useful technique for identifying migrants and, potentially, their homelands. In this study, the first such global survey, we draw on published human tooth enamel and bone bioapatite data to explore the validity of using oxygen isotope analyses to identify migrants in the archaeological record. We use human δ18O results to show that there are large variations in human oxygen isotope values within a population sample. This may relate to physiological factors influencing the preservation of the primary isotope signal, or due to human activities (such as brewing, boiling, stewing, differential access to water sources and so on) causing variation in ingested water and food isotope values. We compare the number of outliers identified using various statistical methods. We determine that the most appropriate method for identifying migrants is dependent on the data but is likely to be the IQR or median absolute deviation from the median under most archaeological circumstances. Finally, through a spatial assessment of the dataset, we show that the degree of overlap in human isotope values from different locations across Europe is such that identifying individuals’ homelands on the basis of oxygen isotope analysis alone is not possible for the regions analysed to date. Oxygen isotope analysis is a valid method for identifying first-generation migrants from an archaeological site when used appropriately, however it is difficult to identify migrants using statistical methods for a sample size of less than c. 25 individuals. In the absence of local previous analyses, each sample should be treated as an individual dataset and statistical techniques can be used to identify migrants, but in most cases pinpointing a specific homeland should not be attempted. PMID:27124001
Cundell, A M; Bean, R; Massimore, L; Maier, C
1998-01-01
To determine the relationship between the sampling time of the environmental monitoring, i.e., viable counts, in aseptic filling areas and the microbial count and frequency of alerts for air, surface and personnel microbial monitoring, statistical analyses were conducted on 1) the frequency of alerts versus the time of day for routine environmental sampling conducted in calendar year 1994, and 2) environmental monitoring data collected at 30-minute intervals during routine aseptic filling operations over two separate days in four different clean rooms with multiple shifts and equipment set-ups at a parenteral manufacturing facility. Statistical analyses showed, except for one floor location that had significantly higher number of counts but no alert or action level samplings in the first two hours of operation, there was no relationship between the number of counts and the time of sampling. Further studies over a 30-day period at the floor location showed no relationship between time of sampling and microbial counts. The conclusion reached in the study was that there is no worst case time for environmental monitoring at that facility and that sampling any time during the aseptic filling operation will give a satisfactory measure of the microbial cleanliness in the clean room during the set-up and aseptic filling operation.
NASA Astrophysics Data System (ADS)
Medyńska-Gulij, Beata; Cybulski, Paweł
2016-06-01
This paper analyses the use of table visual variables of statistical data of hospital beds as an important tool for revealing spatio-temporal dependencies. It is argued that some of conclusions from the data about public health and public expenditure on health have a spatio-temporal reference. Different from previous studies, this article adopts combination of cartographic pragmatics and spatial visualization with previous conclusions made in public health literature. While the significant conclusions about health care and economic factors has been highlighted in research papers, this article is the first to apply visual analysis to statistical table together with maps which is called previsualisation.
ERIC Educational Resources Information Center
Cooper, Harris; Patall, Erika A.
2009-01-01
The authors describe the relative benefits of conducting meta-analyses with (a) individual participant data (IPD) gathered from the constituent studies and (b) aggregated data (AD), or the group-level statistics (in particular, effect sizes) that appear in reports of a study's results. Given that both IPD and AD are equally available,…
Determinants of Demand for Private Supplementary Tutoring in China: Findings from a National Survey
ERIC Educational Resources Information Center
Liu, Junyan; Bray, Mark
2017-01-01
Private tutoring has expanded and intensified in China. However, no government statistical data or other empirical studies fully capture its extent and characteristics. This paper analyses private tutoring received by students in Grades 1-12 as indicated by a nationwide representative survey entitled China Family Panel Studies. The paper employs a…
ERIC Educational Resources Information Center
Eidizadeh, Rosa; Salehzadeh, Reza; Chitsaz Esfahani, Ali
2017-01-01
Purpose: This paper aims to study the role of business intelligence, knowledge sharing and organisational innovation on gaining competitive advantage. Design/Methodology/Approach: The statistical population of the study was the managers and the specialists of some export companies of which 213 persons participated in this research. Path analysis…
ERIC Educational Resources Information Center
Young, Tabitha L.; Gutierrez, Daniel; Hagedorn, W. Bryce
2013-01-01
This study investigated the relationships between motivational interviewing (MI) and client symptoms, attendance, and satisfaction. Seventy-nine clients attending a university-based counseling center were purposefully assigned to treatment or control conditions. Statistical analyses revealed client symptoms in both groups improved. However,…
Statistical methods for analysing responses of wildlife to human disturbance.
Haiganoush K. Preisler; Alan A. Ager; Michael J. Wisdom
2006-01-01
1. Off-road recreation is increasing rapidly in many areas of the world, and effects on wildlife can be highly detrimental. Consequently, we have developed methods for studying wildlife responses to off-road recreation with the use of new technologies that allow frequent and accurate monitoring of human-wildlife interactions. To illustrate these methods, we studied the...
Association between sleep difficulties as well as duration and hypertension: is BMI a mediator?
Carrillo-Larco, R M; Bernabe-Ortiz, A; Sacksteder, K A; Diez-Canseco, F; Cárdenas, M K; Gilman, R H; Miranda, J J
2017-01-01
Sleep difficulties and short sleep duration have been associated with hypertension. Though body mass index (BMI) may be a mediator variable, the mediation effect has not been defined. We aimed to assess the association between sleep duration and sleep difficulties with hypertension, to determine if BMI is a mediator variable, and to quantify the mediation effect. We conducted a mediation analysis and calculated prevalence ratios with 95% confidence intervals. The exposure variables were sleep duration and sleep difficulties, and the outcome was hypertension. Sleep difficulties were statistically significantly associated with a 43% higher prevalence of hypertension in multivariable analyses; results were not statistically significant for sleep duration. In these analyses, and in sex-specific subgroup analyses, we found no strong evidence that BMI mediated the association between sleep indices and risk of hypertension. Our findings suggest that BMI does not appear to mediate the association between sleep patterns and hypertension. These results highlight the need to further study the mechanisms underlying the relationship between sleep patterns and cardiovascular risk factors.
A multicenter study of viable PCR using propidium monoazide to detect Legionella in water samples.
Scaturro, Maria; Fontana, Stefano; Dell'eva, Italo; Helfer, Fabrizia; Marchio, Michele; Stefanetti, Maria Vittoria; Cavallaro, Mario; Miglietta, Marilena; Montagna, Maria Teresa; De Giglio, Osvalda; Cuna, Teresa; Chetti, Leonarda; Sabattini, Maria Antonietta Bucci; Carlotti, Michela; Viggiani, Mariagabriella; Stenico, Alberta; Romanin, Elisa; Bonanni, Emma; Ottaviano, Claudio; Franzin, Laura; Avanzini, Claudio; Demarie, Valerio; Corbella, Marta; Cambieri, Patrizia; Marone, Piero; Rota, Maria Cristina; Bella, Antonino; Ricci, Maria Luisa
2016-07-01
Legionella quantification in environmental samples is overestimated by qPCR. Combination with a viable dye, such as Propidium monoazide (PMA), could make qPCR (named then vPCR) very reliable. In this multicentre study 717 artificial water samples, spiked with fixed concentrations of Legionella and interfering bacterial flora, were analysed by qPCR, vPCR and culture and data were compared by statistical analysis. A heat-treatment at 55 °C for 10 minutes was also performed to obtain viable and not-viable bacteria. When data of vPCR were compared with those of culture and qPCR, statistical analysis showed significant differences (P < 0.001). However, although the heat-treatment caused an abatement of CFU/mL ≤1 to 1 log10 unit, the comparison between untreated and heat-treated samples analysed by vPCR highlighted non-significant differences (P > 0.05). Overall this study provided a good experimental reproducibility of vPCR but also highlighted limits of PMA in the discriminating capability of dead and live bacteria, making vPCR not completely reliable. Copyright © 2016 Elsevier Inc. All rights reserved.
Petrovičová, Andrea; Kurča, Egon; Brozman, Miroslav; Hasilla, Jozef; Vahala, Pavel; Blaško, Peter; Andrášová, Andrea; Hatala, Robert; Urban, Luboš; Sivák, Štefan
2015-12-03
Cardio-embolic etiology is the most frequently predicted cause of cryptogenic stroke/TIA. Detection of occult paroxysmal atrial fibrillation is crucial for selection of appropriate medication. Enrolment of eligible cryptogenic stroke and TIA patients began in 2014 and will continue until 2018. The patients undergo long-term (12 months) ECG monitoring (implantable loop recorder) and testing for PITX2 (chromosome 4q25) and ZFHX3 (chromosome 16q22) gene mutations. There will be an appropriate control group of age- and sex-matched healthy volunteers. To analyse the results descriptive statistics, statistical tests for group differences, and correlation analyses will be used. In our study we are focusing on a possible correlation between detection of atrial fibrillation by an implantable ECG recorder, and PITX2 and/or ZFHX3 gene mutations in cryptogenic stroke/TIA patients. A correlation could lead to implementation of this genomic approach to cryptogenic stroke/TIA diagnostics and management. The results will be published in 2018. ClinicalTrials.gov: NCT02216370 .
Taylor, Janice A; Shaw, Christiana M; Tan, Sanda A; Falcone, John L
2018-01-01
To define resources deemed most important to medical students on their general surgery clerkship, we evaluated their material utilization. A prospective study was conducted amongst third-year medical students using a 20-item survey. Descriptive statistics were performed on the demographics. Kruskal-Wallis and Mann-Whitney analyses were performed on the Likert responses (α = 0.05). Survey response was 69.2%. Use of review books and Internet was significantly higher compared to all other resources (p < 0.05). Wikipedia was the most used Internet source (39.1%). 56% never used textbooks. Analyses of surgery subject exam (NBME) results or intended specialty with resources used showed no statistical relationship (all p > 0.05). Resources used by students reflect access to high-yield material and increased Internet use. The Internet and review books were used more than the recommended textbook; NBME results were not affected. Understanding study habits and resource use will help guide curricular development and students' self-regulated learning. Copyright © 2017 Elsevier Inc. All rights reserved.
Sieve analysis in HIV-1 vaccine efficacy trials
Edlefsen, Paul T.; Gilbert, Peter B.; Rolland, Morgane
2013-01-01
Purpose of review The genetic characterization of HIV-1 breakthrough infections in vaccine and placebo recipients offers new ways to assess vaccine efficacy trials. Statistical and sequence analysis methods provide opportunities to mine the mechanisms behind the effect of an HIV vaccine. Recent findings The release of results from two HIV-1 vaccine efficacy trials, Step/HVTN-502 and RV144, led to numerous studies in the last five years, including efforts to sequence HIV-1 breakthrough infections and compare viral characteristics between the vaccine and placebo groups. Novel genetic and statistical analysis methods uncovered features that distinguished founder viruses isolated from vaccinees from those isolated from placebo recipients, and identified HIV-1 genetic targets of vaccine-induced immune responses. Summary Studies of HIV-1 breakthrough infections in vaccine efficacy trials can provide an independent confirmation to correlates of risk studies, as they take advantage of vaccine/placebo comparisons while correlates of risk analyses are limited to vaccine recipients. Through the identification of viral determinants impacted by vaccine-mediated host immune responses, sieve analyses can shed light on potential mechanisms of vaccine protection. PMID:23719202
Sieve analysis in HIV-1 vaccine efficacy trials.
Edlefsen, Paul T; Gilbert, Peter B; Rolland, Morgane
2013-09-01
The genetic characterization of HIV-1 breakthrough infections in vaccine and placebo recipients offers new ways to assess vaccine efficacy trials. Statistical and sequence analysis methods provide opportunities to mine the mechanisms behind the effect of an HIV vaccine. The release of results from two HIV-1 vaccine efficacy trials, Step/HVTN-502 (HIV Vaccine Trials Network-502) and RV144, led to numerous studies in the last 5 years, including efforts to sequence HIV-1 breakthrough infections and compare viral characteristics between the vaccine and placebo groups. Novel genetic and statistical analysis methods uncovered features that distinguished founder viruses isolated from vaccinees from those isolated from placebo recipients, and identified HIV-1 genetic targets of vaccine-induced immune responses. Studies of HIV-1 breakthrough infections in vaccine efficacy trials can provide an independent confirmation to correlates of risk studies, as they take advantage of vaccine/placebo comparisons, whereas correlates of risk analyses are limited to vaccine recipients. Through the identification of viral determinants impacted by vaccine-mediated host immune responses, sieve analyses can shed light on potential mechanisms of vaccine protection.
NASA Technical Reports Server (NTRS)
Morrissey, L. A.; Weinstock, K. J.; Mouat, D. A.; Card, D. H.
1984-01-01
An evaluation of Thematic Mapper Simulator (TMS) data for the geobotanical discrimination of rock types based on vegetative cover characteristics is addressed in this research. A methodology for accomplishing this evaluation utilizing univariate and multivariate techniques is presented. TMS data acquired with a Daedalus DEI-1260 multispectral scanner were integrated with vegetation and geologic information for subsequent statistical analyses, which included a chi-square test, an analysis of variance, stepwise discriminant analysis, and Duncan's multiple range test. Results indicate that ultramafic rock types are spectrally separable from nonultramafics based on vegetative cover through the use of statistical analyses.
Enabling a Comprehensive Teaching Strategy: Video Lectures
ERIC Educational Resources Information Center
Brecht, H. David; Ogilby, Suzanne M.
2008-01-01
This study empirically tests the feasibility and effectiveness of video lectures as a form of video instruction that enables a comprehensive teaching strategy used throughout a traditional classroom course. It examines student use patterns and the videos' effects on student learning, using qualitative and nonparametric statistical analyses of…
NEUROBEHAVIORAL EVALUATIONS OF BINARY AND TERTIARY MIXTURES OF CHEMICALS: LESSIONS LEARNING.
The classical approach to the statistical analysis of binary chemical mixtures is to construct full dose-response curves for one compound in the presence of a range of doses of the second compound (isobolographic analyses). For interaction studies using more than two chemicals, ...
DOT National Transportation Integrated Search
2016-08-01
This study conducted an analysis of the SCDOT HMA specification. A Research Steering Committee provided oversight : of the process. The research process included extensive statistical analyses of test data supplied by SCDOT. : A total of 2,789 AC tes...
Bynum, T E; Koch, G G
1991-08-08
We sought to compare the efficacy of sucralfate to placebo for the prevention of duodenal ulcer recurrence and to determine that the efficacy of sucralfate was due to a true reduction in ulcer prevalence and not due to secondary effects such as analgesic activity or accelerated healing. This was a double-blind, randomized, placebo-controlled, parallel groups, multicenter clinical study with 254 patients. All patients had a past history of at least two duodenal ulcers with at least one ulcer diagnosed by endoscopic examination 3 months or less before the start of the study. Complete ulcer healing without erosions was required to enter the study. Sucralfate or placebo were dosed as a 1-g tablet twice a day for 4 months, or until ulcer recurrence. Endoscopic examinations once a month and when symptoms developed determined the presence or absence of duodenal ulcers. If a patient developed an ulcer between monthly scheduled visits, the patient was dosed with a 1-g sucralfate tablet twice a day until the next scheduled visit. Statistical analyses of the results determined the efficacy of sucralfate compared with placebo for preventing duodenal ulcer recurrence. Comparisons of therapeutic agents for preventing duodenal ulcers have usually been made by testing for statistical differences in the cumulative rates for all ulcers developed during a follow-up period, regardless of the time of detection. Statistical experts at the United States Food and Drug Administration (FDA) and on the FDA Advisory Panel expressed doubts about clinical study results based on this type of analysis. They suggested three possible mechanisms for reducing the number of observed ulcers: (a) analgesic effects, (b) accelerated healing, and (c) true ulcer prevention. Traditional ulcer analysis could miss recurring ulcers due to an analgesic effect or accelerated healing. Point-prevalence analysis could miss recurring ulcers due to accelerated healing between endoscopic examinations. Maximum ulcer analyses, a novel statistical method, eliminated analgesic effects by regularly scheduled endoscopies and accelerated healing of recurring ulcers by frequent endoscopies and an open-label phase. Maximum ulcer analysis reflects true ulcer recurrence and prevention. Sucralfate was significantly superior to placebo in reducing ulcer prevalence by all analyses. Significance (p less than 0.05) was found at months 3 and 4 for all analyses. All months were significant in the traditional analysis, months 2-4 in point-prevalence analysis, and months 3-4 in the maximal ulcer prevalence analysis. Sucralfate was shown to be effective for the prevention of duodenal ulcer recurrence by a true reduction in new ulcer development.
Han, Kyunghwa; Jung, Inkyung
2018-05-01
This review article presents an assessment of trends in statistical methods and an evaluation of their appropriateness in articles published in the Archives of Plastic Surgery (APS) from 2012 to 2017. We reviewed 388 original articles published in APS between 2012 and 2017. We categorized the articles that used statistical methods according to the type of statistical method, the number of statistical methods, and the type of statistical software used. We checked whether there were errors in the description of statistical methods and results. A total of 230 articles (59.3%) published in APS between 2012 and 2017 used one or more statistical method. Within these articles, there were 261 applications of statistical methods with continuous or ordinal outcomes, and 139 applications of statistical methods with categorical outcome. The Pearson chi-square test (17.4%) and the Mann-Whitney U test (14.4%) were the most frequently used methods. Errors in describing statistical methods and results were found in 133 of the 230 articles (57.8%). Inadequate description of P-values was the most common error (39.1%). Among the 230 articles that used statistical methods, 71.7% provided details about the statistical software programs used for the analyses. SPSS was predominantly used in the articles that presented statistical analyses. We found that the use of statistical methods in APS has increased over the last 6 years. It seems that researchers have been paying more attention to the proper use of statistics in recent years. It is expected that these positive trends will continue in APS.
Kratochwill, Thomas R; Levin, Joel R
2014-04-01
In this commentary, we add to the spirit of the articles appearing in the special series devoted to meta- and statistical analysis of single-case intervention-design data. Following a brief discussion of historical factors leading to our initial involvement in statistical analysis of such data, we discuss: (a) the value added by including statistical-analysis recommendations in the What Works Clearinghouse Standards for single-case intervention designs; (b) the importance of visual analysis in single-case intervention research, along with the distinctive role that could be played by single-case effect-size measures; and (c) the elevated internal validity and statistical-conclusion validity afforded by the incorporation of various forms of randomization into basic single-case design structures. For the future, we envision more widespread application of quantitative analyses, as critical adjuncts to visual analysis, in both primary single-case intervention research studies and literature reviews in the behavioral, educational, and health sciences. Copyright © 2014 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.
Cluster mass inference via random field theory.
Zhang, Hui; Nichols, Thomas E; Johnson, Timothy D
2009-01-01
Cluster extent and voxel intensity are two widely used statistics in neuroimaging inference. Cluster extent is sensitive to spatially extended signals while voxel intensity is better for intense but focal signals. In order to leverage strength from both statistics, several nonparametric permutation methods have been proposed to combine the two methods. Simulation studies have shown that of the different cluster permutation methods, the cluster mass statistic is generally the best. However, to date, there is no parametric cluster mass inference available. In this paper, we propose a cluster mass inference method based on random field theory (RFT). We develop this method for Gaussian images, evaluate it on Gaussian and Gaussianized t-statistic images and investigate its statistical properties via simulation studies and real data. Simulation results show that the method is valid under the null hypothesis and demonstrate that it can be more powerful than the cluster extent inference method. Further, analyses with a single subject and a group fMRI dataset demonstrate better power than traditional cluster size inference, and good accuracy relative to a gold-standard permutation test.
Wijeysundera, Duminda N; Austin, Peter C; Hux, Janet E; Beattie, W Scott; Laupacis, Andreas
2009-01-01
Randomized trials generally use "frequentist" statistics based on P-values and 95% confidence intervals. Frequentist methods have limitations that might be overcome, in part, by Bayesian inference. To illustrate these advantages, we re-analyzed randomized trials published in four general medical journals during 2004. We used Medline to identify randomized superiority trials with two parallel arms, individual-level randomization and dichotomous or time-to-event primary outcomes. Studies with P<0.05 in favor of the intervention were deemed "positive"; otherwise, they were "negative." We used several prior distributions and exact conjugate analyses to calculate Bayesian posterior probabilities for clinically relevant effects. Of 88 included studies, 39 were positive using a frequentist analysis. Although the Bayesian posterior probabilities of any benefit (relative risk or hazard ratio<1) were high in positive studies, these probabilities were lower and variable for larger benefits. The positive studies had only moderate probabilities for exceeding the effects that were assumed for calculating the sample size. By comparison, there were moderate probabilities of any benefit in negative studies. Bayesian and frequentist analyses complement each other when interpreting the results of randomized trials. Future reports of randomized trials should include both.
Lee, Yangchool; Jeoung, Bogja
2016-12-01
The purpose of this study was to determine the relationship between the motor skills and the behavior problems of students with intellectual disabilities. The study participants were 117 students with intellectual disabilities who were between 7 and 25 years old (male, n=79; female, n=38) and attending special education schools in South Korea. Motor skill abilities were assessed by using the second version of the Bruininks-Oseretsky test of motor proficiency, which includes subtests in fine motor control, manual coordination, body coordination, strength, and agility. Data were analyzed with SPSS IBM 21 by using correlation and regression analyses, and the significance level was set at P <0.05. The results showed that fine motor precision and integration had a statistically significant influence on aggressive behavior. Manual dexterity showed a statistically significant influence on somatic complaint and anxiety/depression, and bilateral coordination had a statistically significant influence on social problems, attention problem, and aggressive behavior. Our results showed that balance had a statistically significant influence on social problems and aggressive behavior, and speed and agility had a statistically significant influence on social problems and aggressive behavior. Upper limb coordination and strength had a statistically significant influence on social problems.
Castro, Marcelo P; Pataky, Todd C; Sole, Gisela; Vilas-Boas, Joao Paulo
2015-07-16
Ground reaction force (GRF) data from men and women are commonly pooled for analyses. However, it may not be justifiable to pool sexes on the basis of discrete parameters extracted from continuous GRF gait waveforms because this can miss continuous effects. Forty healthy participants (20 men and 20 women) walked at a cadence of 100 steps per minute across two force plates, recording GRFs. Two statistical methods were used to test the null hypothesis of no mean GRF differences between sexes: (i) Statistical Parametric Mapping-using the entire three-component GRF waveform; and (ii) traditional approach-using the first and second vertical GRF peaks. Statistical Parametric Mapping results suggested large sex differences, which post-hoc analyses suggested were due predominantly to higher anterior-posterior and vertical GRFs in early stance in women compared to men. Statistically significant differences were observed for the first GRF peak and similar values for the second GRF peak. These contrasting results emphasise that different parts of the waveform have different signal strengths and thus that one may use the traditional approach to choose arbitrary metrics and make arbitrary conclusions. We suggest that researchers and clinicians consider both the entire gait waveforms and sex-specificity when analysing GRF data. Copyright © 2015 Elsevier Ltd. All rights reserved.
ERIC Educational Resources Information Center
Petocz, Peter; Sowey, Eric
2012-01-01
The term "data snooping" refers to the practice of choosing which statistical analyses to apply to a set of data after having first looked at those data. Data snooping contradicts a fundamental precept of applied statistics, that the scheme of analysis is to be planned in advance. In this column, the authors shall elucidate the…
The Empirical Nature and Statistical Treatment of Missing Data
ERIC Educational Resources Information Center
Tannenbaum, Christyn E.
2009-01-01
Introduction. Missing data is a common problem in research and can produce severely misleading analyses, including biased estimates of statistical parameters, and erroneous conclusions. In its 1999 report, the APA Task Force on Statistical Inference encouraged authors to report complications such as missing data and discouraged the use of…
Statistical power analysis in wildlife research
Steidl, R.J.; Hayes, J.P.
1997-01-01
Statistical power analysis can be used to increase the efficiency of research efforts and to clarify research results. Power analysis is most valuable in the design or planning phases of research efforts. Such prospective (a priori) power analyses can be used to guide research design and to estimate the number of samples necessary to achieve a high probability of detecting biologically significant effects. Retrospective (a posteriori) power analysis has been advocated as a method to increase information about hypothesis tests that were not rejected. However, estimating power for tests of null hypotheses that were not rejected with the effect size observed in the study is incorrect; these power estimates will always be a??0.50 when bias adjusted and have no relation to true power. Therefore, retrospective power estimates based on the observed effect size for hypothesis tests that were not rejected are misleading; retrospective power estimates are only meaningful when based on effect sizes other than the observed effect size, such as those effect sizes hypothesized to be biologically significant. Retrospective power analysis can be used effectively to estimate the number of samples or effect size that would have been necessary for a completed study to have rejected a specific null hypothesis. Simply presenting confidence intervals can provide additional information about null hypotheses that were not rejected, including information about the size of the true effect and whether or not there is adequate evidence to 'accept' a null hypothesis as true. We suggest that (1) statistical power analyses be routinely incorporated into research planning efforts to increase their efficiency, (2) confidence intervals be used in lieu of retrospective power analyses for null hypotheses that were not rejected to assess the likely size of the true effect, (3) minimum biologically significant effect sizes be used for all power analyses, and (4) if retrospective power estimates are to be reported, then the I?-level, effect sizes, and sample sizes used in calculations must also be reported.
Responses of women to orthostatic and exercise stresses
NASA Technical Reports Server (NTRS)
Hoffler, G. W.; Jackson, M. M.; Johnson, R. L.; Baker, J. T.; Tatro, D.
1990-01-01
The results are presented from a special physiological study of women at the Johnson Space Center in 1976 to 1977. Its purpose was to establish a large (98 subjects) database from normal working women. The data sets are medical historical, clinical, anthropometric, and stress response statistics useful for establishing medical criteria for selecting women astronauts. Stressors were lower body negative pressure and static standing (both orthostatic) and treadmill exercise (ergometric). Data shown are original individual values with analyses and subsets, and statistical summaries and correlations relating to human responses to microgravity. Similarities appear between the characteristics of women in this study and those of women astronauts currently flying in Shuttle crews.
Development of the Statistical Reasoning in Biology Concept Inventory (SRBCI).
Deane, Thomas; Nomme, Kathy; Jeffery, Erica; Pollock, Carol; Birol, Gülnur
2016-01-01
We followed established best practices in concept inventory design and developed a 12-item inventory to assess student ability in statistical reasoning in biology (Statistical Reasoning in Biology Concept Inventory [SRBCI]). It is important to assess student thinking in this conceptual area, because it is a fundamental requirement of being statistically literate and associated skills are needed in almost all walks of life. Despite this, previous work shows that non-expert-like thinking in statistical reasoning is common, even after instruction. As science educators, our goal should be to move students along a novice-to-expert spectrum, which could be achieved with growing experience in statistical reasoning. We used item response theory analyses (the one-parameter Rasch model and associated analyses) to assess responses gathered from biology students in two populations at a large research university in Canada in order to test SRBCI's robustness and sensitivity in capturing useful data relating to the students' conceptual ability in statistical reasoning. Our analyses indicated that SRBCI is a unidimensional construct, with items that vary widely in difficulty and provide useful information about such student ability. SRBCI should be useful as a diagnostic tool in a variety of biology settings and as a means of measuring the success of teaching interventions designed to improve statistical reasoning skills. © 2016 T. Deane et al. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).
Baqué, Michèle; Amendt, Jens
2013-01-01
Developmental data of juvenile blow flies (Diptera: Calliphoridae) are typically used to calculate the age of immature stages found on or around a corpse and thus to estimate a minimum post-mortem interval (PMI(min)). However, many of those data sets don't take into account that immature blow flies grow in a non-linear fashion. Linear models do not supply a sufficient reliability on age estimates and may even lead to an erroneous determination of the PMI(min). According to the Daubert standard and the need for improvements in forensic science, new statistic tools like smoothing methods and mixed models allow the modelling of non-linear relationships and expand the field of statistical analyses. The present study introduces into the background and application of these statistical techniques by analysing a model which describes the development of the forensically important blow fly Calliphora vicina at different temperatures. The comparison of three statistical methods (linear regression, generalised additive modelling and generalised additive mixed modelling) clearly demonstrates that only the latter provided regression parameters that reflect the data adequately. We focus explicitly on both the exploration of the data--to assure their quality and to show the importance of checking it carefully prior to conducting the statistical tests--and the validation of the resulting models. Hence, we present a common method for evaluating and testing forensic entomological data sets by using for the first time generalised additive mixed models.
Hjarsbech, Pernille U; Christensen, Karl Bang; Bjorner, Jakob B; Madsen, Ida E H; Thorsen, Sannie V; Carneiro, Isabella G; Christensen, Ulla; Rugulies, Reiner
2014-03-01
Mental health problems are strong predictors of long-term sickness absence (LTSA). In this study, we investigated whether organizational justice at work - fairness in resolving conflicts and distributing work - prevents risk of LTSA among employees with depressive symptoms. In a longitudinal study with five waves of data collection, we examined a cohort of 1034 employees with depressive symptoms. Depressive symptoms and organizational justice were assessed by self-administered questionnaires and information on LTSA was derived from a national register. Using Poisson regression analyses, we calculated rate ratios (RR) for the prospective association of organizational justice and change in organizational justice with time to onset of LTSA. All analyses were sex stratified. Among men, intermediate levels of organizational justice were statistically significantly associated with a decreased risk of subsequent LTSA after adjustment for covariates [RR 0.49, 95% confidence interval (95% CI) 0.26-0.91]. There was also a decreased risk for men with high levels of organizational justice although these estimates did not reach statistical significance after adjustment (RR 0.47, 95% CI 0.20-1.10). We found no such results for women. In both sexes, neither favorable nor adverse changes in organizational justice were statistically significantly associated with the risk of LTSA. This study shows that organizational justice may have a protective effect on the risk of LTSA among men with depressive symptoms. A protective effect of favorable changes in organizational justice was not found.
Hinman, Sarah E; Blackburn, Jason K; Curtis, Andrew
2006-01-01
Background To better understand the distribution of typhoid outbreaks in Washington, D.C., the U.S. Public Health Service (PHS) conducted four investigations of typhoid fever. These studies included maps of cases reported between 1 May – 31 October 1906 – 1909. These data were entered into a GIS database and analyzed using Ripley's K-function followed by the Gi* statistic in yearly intervals to evaluate spatial clustering, the scale of clustering, and the temporal stability of these clusters. Results The Ripley's K-function indicated no global spatial autocorrelation. The Gi* statistic indicated clustering of typhoid at multiple scales across the four year time period, refuting the conclusions drawn in all four PHS reports concerning the distribution of cases. While the PHS reports suggested an even distribution of the disease, this study quantified both areas of localized disease clustering, as well as mobile larger regions of clustering. Thus, indicating both highly localized and periodic generalized sources of infection within the city. Conclusion The methodology applied in this study was useful for evaluating the spatial distribution and annual-level temporal patterns of typhoid outbreaks in Washington, D.C. from 1906 to 1909. While advanced spatial analyses of historical data sets must be interpreted with caution, this study does suggest that there is utility in these types of analyses and that they provide new insights into the urban patterns of typhoid outbreaks during the early part of the twentieth century. PMID:16566830
Hinman, Sarah E; Blackburn, Jason K; Curtis, Andrew
2006-03-27
To better understand the distribution of typhoid outbreaks in Washington, D.C., the U.S. Public Health Service (PHS) conducted four investigations of typhoid fever. These studies included maps of cases reported between 1 May - 31 October 1906 - 1909. These data were entered into a GIS database and analyzed using Ripley's K-function followed by the Gi* statistic in yearly intervals to evaluate spatial clustering, the scale of clustering, and the temporal stability of these clusters. The Ripley's K-function indicated no global spatial autocorrelation. The Gi* statistic indicated clustering of typhoid at multiple scales across the four year time period, refuting the conclusions drawn in all four PHS reports concerning the distribution of cases. While the PHS reports suggested an even distribution of the disease, this study quantified both areas of localized disease clustering, as well as mobile larger regions of clustering. Thus, indicating both highly localized and periodic generalized sources of infection within the city. The methodology applied in this study was useful for evaluating the spatial distribution and annual-level temporal patterns of typhoid outbreaks in Washington, D.C. from 1906 to 1909. While advanced spatial analyses of historical data sets must be interpreted with caution, this study does suggest that there is utility in these types of analyses and that they provide new insights into the urban patterns of typhoid outbreaks during the early part of the twentieth century.
Quality control and conduct of genome-wide association meta-analyses.
Winkler, Thomas W; Day, Felix R; Croteau-Chonka, Damien C; Wood, Andrew R; Locke, Adam E; Mägi, Reedik; Ferreira, Teresa; Fall, Tove; Graff, Mariaelisa; Justice, Anne E; Luan, Jian'an; Gustafsson, Stefan; Randall, Joshua C; Vedantam, Sailaja; Workalemahu, Tsegaselassie; Kilpeläinen, Tuomas O; Scherag, André; Esko, Tonu; Kutalik, Zoltán; Heid, Iris M; Loos, Ruth J F
2014-05-01
Rigorous organization and quality control (QC) are necessary to facilitate successful genome-wide association meta-analyses (GWAMAs) of statistics aggregated across multiple genome-wide association studies. This protocol provides guidelines for (i) organizational aspects of GWAMAs, and for (ii) QC at the study file level, the meta-level across studies and the meta-analysis output level. Real-world examples highlight issues experienced and solutions developed by the GIANT Consortium that has conducted meta-analyses including data from 125 studies comprising more than 330,000 individuals. We provide a general protocol for conducting GWAMAs and carrying out QC to minimize errors and to guarantee maximum use of the data. We also include details for the use of a powerful and flexible software package called EasyQC. Precise timings will be greatly influenced by consortium size. For consortia of comparable size to the GIANT Consortium, this protocol takes a minimum of about 10 months to complete.
Quality control and conduct of genome-wide association meta-analyses
Winkler, Thomas W; Day, Felix R; Croteau-Chonka, Damien C; Wood, Andrew R; Locke, Adam E; Mägi, Reedik; Ferreira, Teresa; Fall, Tove; Graff, Mariaelisa; Justice, Anne E; Luan, Jian'an; Gustafsson, Stefan; Randall, Joshua C; Vedantam, Sailaja; Workalemahu, Tsegaselassie; Kilpeläinen, Tuomas O; Scherag, André; Esko, Tonu; Kutalik, Zoltán; Heid, Iris M; Loos, Ruth JF
2014-01-01
Rigorous organization and quality control (QC) are necessary to facilitate successful genome-wide association meta-analyses (GWAMAs) of statistics aggregated across multiple genome-wide association studies. This protocol provides guidelines for [1] organizational aspects of GWAMAs, and for [2] QC at the study file level, the meta-level across studies, and the meta-analysis output level. Real–world examples highlight issues experienced and solutions developed by the GIANT Consortium that has conducted meta-analyses including data from 125 studies comprising more than 330,000 individuals. We provide a general protocol for conducting GWAMAs and carrying out QC to minimize errors and to guarantee maximum use of the data. We also include details for use of a powerful and flexible software package called EasyQC. For consortia of comparable size to the GIANT consortium, the present protocol takes a minimum of about 10 months to complete. PMID:24762786
Time Series Expression Analyses Using RNA-seq: A Statistical Approach
Oh, Sunghee; Song, Seongho; Grabowski, Gregory; Zhao, Hongyu; Noonan, James P.
2013-01-01
RNA-seq is becoming the de facto standard approach for transcriptome analysis with ever-reducing cost. It has considerable advantages over conventional technologies (microarrays) because it allows for direct identification and quantification of transcripts. Many time series RNA-seq datasets have been collected to study the dynamic regulations of transcripts. However, statistically rigorous and computationally efficient methods are needed to explore the time-dependent changes of gene expression in biological systems. These methods should explicitly account for the dependencies of expression patterns across time points. Here, we discuss several methods that can be applied to model timecourse RNA-seq data, including statistical evolutionary trajectory index (SETI), autoregressive time-lagged regression (AR(1)), and hidden Markov model (HMM) approaches. We use three real datasets and simulation studies to demonstrate the utility of these dynamic methods in temporal analysis. PMID:23586021
Time series expression analyses using RNA-seq: a statistical approach.
Oh, Sunghee; Song, Seongho; Grabowski, Gregory; Zhao, Hongyu; Noonan, James P
2013-01-01
RNA-seq is becoming the de facto standard approach for transcriptome analysis with ever-reducing cost. It has considerable advantages over conventional technologies (microarrays) because it allows for direct identification and quantification of transcripts. Many time series RNA-seq datasets have been collected to study the dynamic regulations of transcripts. However, statistically rigorous and computationally efficient methods are needed to explore the time-dependent changes of gene expression in biological systems. These methods should explicitly account for the dependencies of expression patterns across time points. Here, we discuss several methods that can be applied to model timecourse RNA-seq data, including statistical evolutionary trajectory index (SETI), autoregressive time-lagged regression (AR(1)), and hidden Markov model (HMM) approaches. We use three real datasets and simulation studies to demonstrate the utility of these dynamic methods in temporal analysis.
Damiani, Lucas Petri; Berwanger, Otavio; Paisani, Denise; Laranjeira, Ligia Nasi; Suzumura, Erica Aranha; Amato, Marcelo Britto Passos; Carvalho, Carlos Roberto Ribeiro; Cavalcanti, Alexandre Biasi
2017-01-01
Background The Alveolar Recruitment for Acute Respiratory Distress Syndrome Trial (ART) is an international multicenter randomized pragmatic controlled trial with allocation concealment involving 120 intensive care units in Brazil, Argentina, Colombia, Italy, Poland, Portugal, Malaysia, Spain, and Uruguay. The primary objective of ART is to determine whether maximum stepwise alveolar recruitment associated with PEEP titration, adjusted according to the static compliance of the respiratory system (ART strategy), is able to increase 28-day survival in patients with acute respiratory distress syndrome compared to conventional treatment (ARDSNet strategy). Objective To describe the data management process and statistical analysis plan. Methods The statistical analysis plan was designed by the trial executive committee and reviewed and approved by the trial steering committee. We provide an overview of the trial design with a special focus on describing the primary (28-day survival) and secondary outcomes. We describe our data management process, data monitoring committee, interim analyses, and sample size calculation. We describe our planned statistical analyses for primary and secondary outcomes as well as pre-specified subgroup analyses. We also provide details for presenting results, including mock tables for baseline characteristics, adherence to the protocol and effect on clinical outcomes. Conclusion According to best trial practice, we report our statistical analysis plan and data management plan prior to locking the database and beginning analyses. We anticipate that this document will prevent analysis bias and enhance the utility of the reported results. Trial registration ClinicalTrials.gov number, NCT01374022. PMID:28977255
Tips and Tricks for Successful Application of Statistical Methods to Biological Data.
Schlenker, Evelyn
2016-01-01
This chapter discusses experimental design and use of statistics to describe characteristics of data (descriptive statistics) and inferential statistics that test the hypothesis posed by the investigator. Inferential statistics, based on probability distributions, depend upon the type and distribution of the data. For data that are continuous, randomly and independently selected, as well as normally distributed more powerful parametric tests such as Student's t test and analysis of variance (ANOVA) can be used. For non-normally distributed or skewed data, transformation of the data (using logarithms) may normalize the data allowing use of parametric tests. Alternatively, with skewed data nonparametric tests can be utilized, some of which rely on data that are ranked prior to statistical analysis. Experimental designs and analyses need to balance between committing type 1 errors (false positives) and type 2 errors (false negatives). For a variety of clinical studies that determine risk or benefit, relative risk ratios (random clinical trials and cohort studies) or odds ratios (case-control studies) are utilized. Although both use 2 × 2 tables, their premise and calculations differ. Finally, special statistical methods are applied to microarray and proteomics data, since the large number of genes or proteins evaluated increase the likelihood of false discoveries. Additional studies in separate samples are used to verify microarray and proteomic data. Examples in this chapter and references are available to help continued investigation of experimental designs and appropriate data analysis.
Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.
Faul, Franz; Erdfelder, Edgar; Buchner, Axel; Lang, Albert-Georg
2009-11-01
G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.
Behind the statistics: the ethnography of suicide in Palestine.
Dabbagh, Nadia
2012-06-01
As part of the first anthropological study on suicide in the modern Arab world, statistics gathered from the Ramallah region of the West Bank in Palestine painted an apparently remarkably similar picture to that found in Western countries such as the UK and France. More men than women completed suicide, more women than men attempted suicide. Men used more violent methods such as hanging and women softer methods such as medication overdose. Completed suicide was higher in the older age range, attempted suicide in the younger. However, ethnographic fieldwork and detailed examination of the case studies and suicide narratives gathered and analysed within the cultural, political and economic contexts illustrated more starkly the differences in suicidal practices between Palestinian West Bank society of the 1990s and other regions of the world. The central argument of the paper is that although statistics tell a very important story, ethnography uncovers a multitude of stories 'behind the statistics', and thus helps us to make sense of both cultural context and subjective experience.
Wingate, Peter H; Thornton, George C; McIntyre, Kelly S; Frame, Jennifer H
2003-02-01
The present study examined relationships between reduction-in-force (RIF) personnel practices, presentation of statistical evidence, and litigation outcomes. Policy capturing methods were utilized to analyze the components of 115 federal district court opinions involving age discrimination disparate treatment allegations and organizational downsizing. Univariate analyses revealed meaningful links between RIF personnel practices, use of statistical evidence, and judicial verdict. The defendant organization was awarded summary judgment in 73% of the claims included in the study. Judicial decisions in favor of the defendant organization were found to be significantly related to such variables as formal performance appraisal systems, termination decision review within the organization, methods of employee assessment and selection for termination, and the presence of a concrete layoff policy. The use of statistical evidence in ADEA disparate treatment litigation was investigated and found to be a potentially persuasive type of indirect evidence. Legal, personnel, and evidentiary ramifications are reviewed, and a framework of downsizing mechanics emphasizing legal defensibility is presented.
NASA Astrophysics Data System (ADS)
Kaleva Oikarinen, Juho; Järvelä, Sanna; Kaasila, Raimo
2014-04-01
This design-based research project focuses on documenting statistical learning among 16-17-year-old Finnish upper secondary school students (N = 78) in a computer-supported collaborative learning (CSCL) environment. One novel value of this study is in reporting the shift from teacher-led mathematical teaching to autonomous small-group learning in statistics. The main aim of this study is to examine how student collaboration occurs in learning statistics in a CSCL environment. The data include material from videotaped classroom observations and the researcher's notes. In this paper, the inter-subjective phenomena of students' interactions in a CSCL environment are analysed by using a contact summary sheet (CSS). The development of the multi-dimensional coding procedure of the CSS instrument is presented. Aptly selected video episodes were transcribed and coded in terms of conversational acts, which were divided into non-task-related and task-related categories to depict students' levels of collaboration. The results show that collaborative learning (CL) can facilitate cohesion and responsibility and reduce students' feelings of detachment in our classless, periodic school system. The interactive .pdf material and collaboration in small groups enable statistical learning. It is concluded that CSCL is one possible method of promoting statistical teaching. CL using interactive materials seems to foster and facilitate statistical learning processes.
The statistical reporting quality of articles published in 2010 in five dental journals.
Vähänikkilä, Hannu; Tjäderhane, Leo; Nieminen, Pentti
2015-01-01
Statistical methods play an important role in medical and dental research. In earlier studies it has been observed that current use of methods and reporting of statistics are responsible for some of the errors in the interpretation of results. The aim of this study was to investigate the quality of statistical reporting in dental research articles. A total of 200 articles published in 2010 were analysed covering five dental journals: Journal of Dental Research, Caries Research, Community Dentistry and Oral Epidemiology, Journal of Dentistry and Acta Odontologica Scandinavica. Each paper underwent careful scrutiny for the use of statistical methods and reporting. A paper with at least one poor reporting item has been classified as 'problems with reporting statistics' and a paper without any poor reporting item as 'acceptable'. The investigation showed that 18 (9%) papers were acceptable and 182 (91%) papers contained at least one poor reporting item. The proportion of at least one poor reporting item in this survey was high (91%). The authors of dental journals should be encouraged to improve the statistical section of their research articles and to present the results in such a way that it is in line with the policy and presentation of the leading dental journals.
Health Benefits of Dietary Whole Grains: An Umbrella Review of Meta-analyses.
McRae, Marc P
2017-03-01
The purpose of this study is to review the effectiveness of the role of whole grain as a therapeutic agent in type 2 diabetes, cardiovascular disease, cancer, and obesity. An umbrella review of all published meta-analyses was performed. A PubMed search from January 1, 1980, to May 31, 2016, was conducted using the following search strategy: (whole grain OR whole grains) AND (meta-analysis OR systematic review). Only English language publications that provided quantitative statistical analysis on type 2 diabetes, cardiovascular disease, cancer, and weight loss were retrieved. Twenty-one meta-analyses were retrieved for inclusion in this umbrella review, and all the meta-analyses reported statistically significant positive benefits for reducing the incidence of type 2 diabetes (relative risk [RR] = 0.68-0.80), cardiovascular disease (RR = 0.63-0.79), and colorectal, pancreatic, and gastric cancers (RR = 0.57-0.94) and a modest effect on body weight, waist circumference, and body fat mass. Significant reductions in cardiovascular and cancer mortality were also observed (RR = 0.82 and 0.89, respectively). Some problems of heterogeneity, publication bias, and quality assessment were found among the studies. This review suggests that there is some evidence for dietary whole grain intake to be beneficial in the prevention of type 2 diabetes, cardiovascular disease, and colorectal, pancreatic, and gastric cancers. The potential benefits of these findings suggest that the consumption of 2 to 3 servings per day (~45 g) of whole grains may be a justifiable public health goal.
Spatial Autocorrelation Approaches to Testing Residuals from Least Squares Regression.
Chen, Yanguang
2016-01-01
In geo-statistics, the Durbin-Watson test is frequently employed to detect the presence of residual serial correlation from least squares regression analyses. However, the Durbin-Watson statistic is only suitable for ordered time or spatial series. If the variables comprise cross-sectional data coming from spatial random sampling, the test will be ineffectual because the value of Durbin-Watson's statistic depends on the sequence of data points. This paper develops two new statistics for testing serial correlation of residuals from least squares regression based on spatial samples. By analogy with the new form of Moran's index, an autocorrelation coefficient is defined with a standardized residual vector and a normalized spatial weight matrix. Then by analogy with the Durbin-Watson statistic, two types of new serial correlation indices are constructed. As a case study, the two newly presented statistics are applied to a spatial sample of 29 China's regions. These results show that the new spatial autocorrelation models can be used to test the serial correlation of residuals from regression analysis. In practice, the new statistics can make up for the deficiencies of the Durbin-Watson test.
Determinants of antiretroviral therapy coverage in Sub-Saharan Africa
Hoque, Mohammad Zahirul
2015-01-01
Among 35 million people living with the human immunodeficiency virus (HIV) in 2013, only 37% had access to antiretroviral therapy (ART). Despite global concerted efforts to provide the universal access to the ART treatment, the ART coverage varies among countries and regions. At present, there is a lack of systematic empirical analyses on factors that determine the ART coverage. Therefore, the current study aimed to identify the determinants of the ART coverage in 41 countries in Sub-Saharan Africa. It employed statistical analyses for this purpose. Four elements, namely, the HIV prevalence, the level of national income, the level of medical expenditure and the number of nurses, were hypothesised to determine the ART coverage. The findings revealed that among the four proposed determinants only the HIV prevalence had a statistically significant impact on the ART coverage. In other words, the HIV prevalence was the sole determinant of the ART coverage in Sub-Saharan Africa. PMID:26664812
Waller, D.L.; Holland Bartels, L. E.; Mitchell, L.G.
1988-01-01
Glochidia of the endangered unionid mussel Lampsilis higginsi (Lea) are morphologically similar to those of several other species in the upper Mississippi River. Life history details, such as the timing of reproduction and identity of host fish, can be readily studied if the glochidia of L. higginsi can be distinguished from those of related species. Authors used light and scanning electron microscopy and statistical analyses of three shell measurements, shell length, shell height, and hinge length, to compare the glochidia of L. higginsi with those of L. radiata siliquoidea (Barnes), L. ventricosa (Barnes), and Ligumia recta (Lamarck). Glochidia of L. higginsi were differentiated by scanning electron microscopy on the basis of a combined examination of the position of the hinge ligament and the width of dorsal ridges, but were indistinguishable by light microscope examination or by statistical analyses of measurements.
NASA Astrophysics Data System (ADS)
Saini, K. K.; Sehgal, R. K.; Sethi, B. L.
2008-10-01
In this paper major reliability estimators are analyzed and there comparatively result are discussed. There strengths and weaknesses are evaluated in this case study. Each of the reliability estimators has certain advantages and disadvantages. Inter-rater reliability is one of the best ways to estimate reliability when your measure is an observation. However, it requires multiple raters or observers. As an alternative, you could look at the correlation of ratings of the same single observer repeated on two different occasions. Each of the reliability estimators will give a different value for reliability. In general, the test-retest and inter-rater reliability estimates will be lower in value than the parallel forms and internal consistency ones because they involve measuring at different times or with different raters. Since reliability estimates are often used in statistical analyses of quasi-experimental designs.
Vocal training in an anthropometrical aspect.
Wyganowska-Świątkowska, Marzena; Kowalkowska, Iwona; Flicińska-Pamfil, Grażyna; Dąbrowski, Mikołaj; Kopczyński, Przemysław; Wiskirska-Woźnica, Bożena
2017-12-01
As shown in our previous paper, the dimensions of the cerebral parts of the cranium and face of the vocal students were higher than those of the non-singing students. The aim of the present study was to analyse the type of voice and its development depending on selected dimensions. A total of 56 vocal students - 36 women and 20 men - who underwent anthropometric measurements were divided into groups according to their voice type. Two professors of singing made a subjective, independent evaluation of individual students' vocal development progress during the four years of training. The findings were analysed statistically with the current licensed versions of Statistica software. We found statistically significant positive correlation between: the head length, head and face width, depth of upper and middle face, nose length and student's voice development. The dimensions of the head and the face have no impact on type of voice; however, some anatomical characteristics may have impact on voice development.
Difficulties in learning and teaching statistics: teacher views
NASA Astrophysics Data System (ADS)
Koparan, Timur
2015-01-01
The purpose of this study is to define teacher views about the difficulties in learning and teaching middle school statistics subjects. To serve this aim, a number of interviews were conducted with 10 middle school maths teachers in 2011-2012 school year in the province of Trabzon. Of the qualitative descriptive research methods, the semi-structured interview technique was applied in the research. In accordance with the aim, teacher opinions about the statistics subjects were examined and analysed. Similar responses from the teachers were grouped and evaluated. The teachers stated that it was positive that middle school statistics subjects were taught gradually in every grade but some difficulties were experienced in the teaching of this subject. The findings are presented in eight themes which are context, sample, data representation, central tendency and dispersion measure, probability, variance, and other difficulties.
[Clinical research XXIII. From clinical judgment to meta-analyses].
Rivas-Ruiz, Rodolfo; Castelán-Martínez, Osvaldo D; Pérez-Rodríguez, Marcela; Palacios-Cruz, Lino; Noyola-Castillo, Maura E; Talavera, Juan O
2014-01-01
Systematic reviews (SR) are studies made in order to ask clinical questions based on original articles. Meta-analysis (MTA) is the mathematical analysis of SR. These analyses are divided in two groups, those which evaluate the measured results of quantitative variables (for example, the body mass index -BMI-) and those which evaluate qualitative variables (for example, if a patient is alive or dead, or if he is healing or not). Quantitative variables generally use the mean difference analysis and qualitative variables can be performed using several calculations: odds ratio (OR), relative risk (RR), absolute risk reduction (ARR) and hazard ratio (HR). These analyses are represented through forest plots which allow the evaluation of each individual study, as well as the heterogeneity between studies and the overall effect of the intervention. These analyses are mainly based on Student's t test and chi-squared. To take appropriate decisions based on the MTA, it is important to understand the characteristics of statistical methods in order to avoid misinterpretations.
Stewart, Gavin B.; Altman, Douglas G.; Askie, Lisa M.; Duley, Lelia; Simmonds, Mark C.; Stewart, Lesley A.
2012-01-01
Background Individual participant data (IPD) meta-analyses that obtain “raw” data from studies rather than summary data typically adopt a “two-stage” approach to analysis whereby IPD within trials generate summary measures, which are combined using standard meta-analytical methods. Recently, a range of “one-stage” approaches which combine all individual participant data in a single meta-analysis have been suggested as providing a more powerful and flexible approach. However, they are more complex to implement and require statistical support. This study uses a dataset to compare “two-stage” and “one-stage” models of varying complexity, to ascertain whether results obtained from the approaches differ in a clinically meaningful way. Methods and Findings We included data from 24 randomised controlled trials, evaluating antiplatelet agents, for the prevention of pre-eclampsia in pregnancy. We performed two-stage and one-stage IPD meta-analyses to estimate overall treatment effect and to explore potential treatment interactions whereby particular types of women and their babies might benefit differentially from receiving antiplatelets. Two-stage and one-stage approaches gave similar results, showing a benefit of using anti-platelets (Relative risk 0.90, 95% CI 0.84 to 0.97). Neither approach suggested that any particular type of women benefited more or less from antiplatelets. There were no material differences in results between different types of one-stage model. Conclusions For these data, two-stage and one-stage approaches to analysis produce similar results. Although one-stage models offer a flexible environment for exploring model structure and are useful where across study patterns relating to types of participant, intervention and outcome mask similar relationships within trials, the additional insights provided by their usage may not outweigh the costs of statistical support for routine application in syntheses of randomised controlled trials. Researchers considering undertaking an IPD meta-analysis should not necessarily be deterred by a perceived need for sophisticated statistical methods when combining information from large randomised trials. PMID:23056232
SEER Cancer Query Systems (CanQues)
These applications provide access to cancer statistics including incidence, mortality, survival, prevalence, and probability of developing or dying from cancer. Users can display reports of the statistics or extract them for additional analyses.
Understanding Non-Suicidal Self-Injury: Perceptions of School Counselors
ERIC Educational Resources Information Center
Simpson, Chris; Armstrong, Stephen A.; Couch, Lisa; Bore, Samuel K.
2010-01-01
This national exploratory study examined the perceptions of secondary school counselors' (n = 81) understanding of non-suicidal self-injury (NSSI). Two one-way ANOVAs revealed no statistically significant differences between middle and high school counselors on their perceptions of the prevalence of NSSI. Descriptive analyses revealed that a…
Judgmental and Statistical DIF Analyses of the PISA-2003 Mathematics Literacy Items
ERIC Educational Resources Information Center
Yildirim, Huseyin Husnu; Berberoglu, Giray
2009-01-01
Comparisons of human characteristics across different language groups and cultures become more important in today's educational assessment practices as evidenced by the increasing interest in international comparative studies. Within this context, the fairness of the results across different language and cultural groups draws the attention of…
ERIC Educational Resources Information Center
McNeal, Laura R.
2007-01-01
The purpose of this study was to explore what factors served as impediments to institutional efforts to comply with Clery Act guidelines through the perceptions of campus law administrators. Statistical analyses were performed on data collected from an online survey, which was distributed to members of the International Association of Campus Law…
Non-Cognitive Factor Relationships to Hybrid Doctoral Course Satisfaction and Self-Efficacy
ERIC Educational Resources Information Center
Egbert, Jessica Dalby
2013-01-01
Through a quantitative, non-experimental design, the studied explored non-cognitive factor relationships to hybrid doctoral course satisfaction and self-efficacy, including the differences between the online and on-campus components of the student-selected hybrid courses. Descriptive, bivariate, and multivariate statistical analyses were used to…
Modeling Human-Computer Decision Making with Covariance Structure Analysis.
ERIC Educational Resources Information Center
Coovert, Michael D.; And Others
Arguing that sufficient theory exists about the interplay between human information processing, computer systems, and the demands of various tasks to construct useful theories of human-computer interaction, this study presents a structural model of human-computer interaction and reports the results of various statistical analyses of this model.…
Multiplicity Control in Structural Equation Modeling
ERIC Educational Resources Information Center
Cribbie, Robert A.
2007-01-01
Researchers conducting structural equation modeling analyses rarely, if ever, control for the inflated probability of Type I errors when evaluating the statistical significance of multiple parameters in a model. In this study, the Type I error control, power and true model rates of famsilywise and false discovery rate controlling procedures were…
ERIC Educational Resources Information Center
Lang, Quek Choon; Wong, Angela F. L.; Fraser, Barry J.
2005-01-01
This study investigated associations between teacher-student interaction and students' attitudes towards chemistry among 497 tenth grade students from three independent schools in Singapore. Analyses supported the reliability and validity of a 48-item version of the Questionnaire on Teacher Interaction (QTI). Statistically significant gender…
Data Interpretation: Using Probability
ERIC Educational Resources Information Center
Drummond, Gordon B.; Vowler, Sarah L.
2011-01-01
Experimental data are analysed statistically to allow researchers to draw conclusions from a limited set of measurements. The hard fact is that researchers can never be certain that measurements from a sample will exactly reflect the properties of the entire group of possible candidates available to be studied (although using a sample is often the…
Student Evaluation of Instruction: Comparison between In-Class and Online Methods
ERIC Educational Resources Information Center
Capa-Aydin, Yesim
2016-01-01
This study compares student evaluations of instruction that were collected in-class with those gathered through an online survey. The two modes of administration were compared with respect to response rate, psychometric characteristics and mean ratings through different statistical analyses. Findings indicated that in-class evaluations produced a…
Congruence between Disabled Elders and Their Primary Caregivers
ERIC Educational Resources Information Center
Horowitz, Amy; Goodman, Caryn R.; Reinhardt, Joann P.
2004-01-01
Purpose: This study examines the extent and independent correlates of congruence between disabled elders and their caregivers on several aspects of the caregiving experience. Design and Methods: Participants were 117 visually impaired elders and their caregivers. Correlational analyses, kappa statistics, and paired t tests were used to examine the…
Learning Opportunities for Group Learning
ERIC Educational Resources Information Center
Gil, Alfonso J.; Mataveli, Mara
2017-01-01
Purpose: This paper aims to analyse the impact of organizational learning culture and learning facilitators in group learning. Design/methodology/approach: This study was conducted using a survey method applied to a statistically representative sample of employees from Rioja wine companies in Spain. A model was tested using a structural equation…
School Libraries and Science Achievement: A View from Michigan's Middle Schools
ERIC Educational Resources Information Center
Mardis, Marcia
2007-01-01
If strong school library media centers (SLMCs) positively impact middle school student reading achievement, as measured on standardized tests, are they also beneficial for middle school science achievement? To answer this question, the researcher built upon the statistical analyses used in previous school library impact studies with qualitative…
The Role of Sexual Precedence in Verbal Sexual Coercion
ERIC Educational Resources Information Center
Livingston, Jennifer A.; Buddie, Amy M.; Testa, Maria; VanZile-Tamsen, Carol
2004-01-01
Experiences of verbal sexual coercion are common and have potential for negative consequences, yet are not well understood. This study used qualitative and descriptive statistics to examine verbal sexual coercion experiences among a community sample of 114 women and explored the role of sexual precedence in these experiences. Analyses revealed…
Corporal Punishment and Student Outcomes in Rural Schools
ERIC Educational Resources Information Center
Han, Seunghee
2014-01-01
This study examined the effects of corporal punishment on student outcomes in rural schools by analyzing 1,067 samples from the School Survey on Crime and Safety 2007-2008. Results of descriptive statistics and multivariate regression analyses indicated that schools with corporal punishment may decrease students' violent behaviors and…
Indicators are commonly used for evaluating relative sustainability for competing products and processes. When a set of indicators is chosen for a particular system of study, it is important to ensure that they are variable independently of each other. Often the number of indicat...
States-of-Mind Model: Cognitive Balance in the Treatment of Agoraphobia.
ERIC Educational Resources Information Center
Schwartz, Robert M.; Michelson, Larry
1987-01-01
Used states-of-mind model to track therapeutic changes in cognitive balance of 39 agoraphobics. Descriptive and statistical analyses from an outcome study of graduated exposure, relaxation training, and paradoxical intention supported the model. Agoraphobics evinced negative dialogue at pretreatment, positive dialogue at mid and posttreatment, and…
Ethnic Identity and Career Development among First-Year College Students
ERIC Educational Resources Information Center
Duffy, Ryan D.; Klingaman, Elizabeth A.
2009-01-01
The current study explored the relation of ethnic identity achievement and career development progress among a sample of 2,432 first-year college students who completed the Career Decision Profile and Phinney's Multigroup Ethnic Identity Measure. Among students of color, correlational analyses revealed a series of statistically significant, but…
Facilitating the Transition from Bright to Dim Environments
2016-03-04
For the parametric data, a multivariate ANOVA was used in determining the systematic presence of any statistically significant performance differences...performed. All significance levels were p < 0.05, and statistical analyses were performed with the Statistical Package for Social Sciences ( SPSS ...1950. Age changes in rate and level of visual dark adaptation. Journal of Applied Physiology, 2, 407–411. Field, A. 2009. Discovering statistics
Imaging Depression in Adults with ASD
2017-10-01
collected temporally close enough to imaging data in Phase 2 to be confidently incorporated in the planned statistical analyses, and (b) not unduly risk...Phase 2 to be confidently incorporated in the planned statistical analyses, and (b) not unduly risk attrition between Phase 1 and 2, we chose to hold...supervision is ongoing (since 9/2014). • Co-l Dr. Lerner’s 2nd year Clinical Psychology PhD students have participated in ADOS- 2 Introductory Clinical
Schulz, Marcus; Neumann, Daniel; Fleet, David M; Matthies, Michael
2013-12-01
During the last decades, marine pollution with anthropogenic litter has become a worldwide major environmental concern. Standardized monitoring of litter since 2001 on 78 beaches selected within the framework of the Convention for the Protection of the Marine Environment of the North-East Atlantic (OSPAR) has been used to identify temporal trends of marine litter. Based on statistical analyses of this dataset a two-part multi-criteria evaluation system for beach litter pollution of the North-East Atlantic and the North Sea is proposed. Canonical correlation analyses, linear regression analyses, and non-parametric analyses of variance were used to identify different temporal trends. A classification of beaches was derived from cluster analyses and served to define different states of beach quality according to abundances of 17 input variables. The evaluation system is easily applicable and relies on the above-mentioned classification and on significant temporal trends implied by significant rank correlations. Copyright © 2013 Elsevier Ltd. All rights reserved.
Alexander, Dominik D; Miller, Paige E; Van Elswyk, Mary E; Kuratko, Connye N; Bylsma, Lauren C
2017-01-01
To conduct meta-analyses of randomized controlled trials (RCTs) to estimate the effect of eicosapentaenoic and docosahexaenoic acid (EPA+DHA) on coronary heart disease (CHD), and to conduct meta-analyses of prospective cohort studies to estimate the association between EPA+DHA intake and CHD risk. A systematic literature search of Ovid/Medline, PubMed, Embase, and the Cochrane Library from January 1, 1947, to November 2, 2015, was conducted; 18 RCTs and 16 prospective cohort studies examining EPA+DHA from foods or supplements and CHD, including myocardial infarction, sudden cardiac death, coronary death, and angina, were identified. Random-effects meta-analysis models were used to generate summary relative risk estimates (SRREs) and 95% CIs. Heterogeneity was examined in subgroup and sensitivity analyses and by meta-regression. Dose-response was evaluated in stratified dose or intake analyses. Publication bias assessments were performed. Among RCTs, there was a nonstatistically significant reduction in CHD risk with EPA+DHA provision (SRRE=0.94; 95% CI, 0.85-1.05). Subgroup analyses of data from RCTs indicated a statistically significant CHD risk reduction with EPA+DHA provision among higher-risk populations, including participants with elevated triglyceride levels (SRRE=0.84; 95% CI, 0.72-0.98) and elevated low-density lipoprotein cholesterol (SRRE=0.86; 95% CI, 0.76-0.98). Meta-analysis of data from prospective cohort studies resulted in a statistically significant SRRE of 0.82 (95% CI, 0.74-0.92) for higher intakes of EPA+DHA and risk of any CHD event. Results indicate that EPA+DHA may be associated with reducing CHD risk, with a greater benefit observed among higher-risk populations in RCTs. Copyright © 2016 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Flores-Marquez, Leticia Elsa; Ramirez Rojaz, Alejandro; Telesca, Luciano
2015-04-01
The study of two statistical approaches is analyzed for two different types of data sets, one is the seismicity generated by the subduction processes occurred at south Pacific coast of Mexico between 2005 and 2012, and the other corresponds to the synthetic seismic data generated by a stick-slip experimental model. The statistical methods used for the present study are the visibility graph in order to investigate the time dynamics of the series and the scaled probability density function in the natural time domain to investigate the critical order of the system. This comparison has the purpose to show the similarities between the dynamical behaviors of both types of data sets, from the point of view of critical systems. The observed behaviors allow us to conclude that the experimental set up globally reproduces the behavior observed in the statistical approaches used to analyses the seismicity of the subduction zone. The present study was supported by the Bilateral Project Italy-Mexico Experimental Stick-slip models of tectonic faults: innovative statistical approaches applied to synthetic seismic sequences, jointly funded by MAECI (Italy) and AMEXCID (Mexico) in the framework of the Bilateral Agreement for Scientific and Technological Cooperation PE 2014-2016.
Khatoon, Farheen
2015-01-01
Background Health care faces challenges due to complications, inefficiencies and other concerns that threaten the safety of patients. Aim The purpose of his study was to identify causes of complications encountered after administration of local anaesthesia for dental and oral surgical procedures and to reduce the incidence of complications by introduction of six sigma methodology. Materials and Methods DMAIC (Define, Measure, Analyse, Improve and Control) process of Six Sigma was taken into consideration to reduce the incidence of complications encountered after administration of local anaesthesia injections for dental and oral surgical procedures using failure mode and effect analysis. Pareto analysis was taken into consideration to analyse the most recurring complications. Paired z-sample test using Minitab Statistical Inference and Fisher’s exact test was used to statistically analyse the obtained data. The p-value <0.05 was considered as significant value. Results Total 54 systemic and 62 local complications occurred during three months of analyse and measure phase. Syncope, failure of anaesthesia, trismus, auto mordeduras and pain at injection site was found to be most recurring complications. Cumulative defective percentage was 7.99 in case of pre-improved data and decreased to 4.58 in the control phase. Estimate for difference was 0.0341228 and 95% lower bound for difference was 0.0193966. p-value was found to be highly significant with p= 0.000. Conclusion The application of six sigma improvement methodology in healthcare tends to deliver consistently better results to the patients as well as hospitals and results in better patient compliance as well as satisfaction. PMID:26816989
Eljamel, M Sam; Mahboob, Syed Osama
2016-12-01
Surgical resection of high-grade gliomas (HGG) is standard therapy because it imparts significant progression free (PFS) and overall survival (OS). However, HGG-tumor margins are indistinguishable from normal brain during surgery. Hence intraoperative technology such as fluorescence (ALA, fluorescein) and intraoperative ultrasound (IoUS) and MRI (IoMRI) has been deployed. This study compares the effectiveness and cost-effectiveness of these technologies. Critical literature review and meta-analyses, using MEDLINE/PubMed service. The list of references in each article was double-checked for any missing references. We included all studies that reported the use of ALA, fluorescein (FLCN), IoUS or IoMRI to guide HGG-surgery. The meta-analyses were conducted according to statistical heterogeneity between studies. If there was no heterogeneity, fixed effects model was used; otherwise, a random effects model was used. Statistical heterogeneity was explored by χ 2 and inconsistency (I 2 ) statistics. To assess cost-effectiveness, we calculated the incremental cost per quality-adjusted life-year (QALY). Gross total resection (GTR) after ALA, FLCN, IoUS and IoMRI was 69.1%, 84.4%, 73.4% and 70% respectively. The differences were not statistically significant. All four techniques led to significant prolongation of PFS and tended to prolong OS. However none of these technologies led to significant prolongation of OS compared to controls. The cost/QALY was $16,218, $3181, $6049 and $32,954 for ALA, FLCN, IoUS and IoMRI respectively. ALA, FLCN, IoUS and IoMRI significantly improve GTR and PFS of HGG. Their incremental cost was below the threshold for cost-effectiveness of HGG-therapy, denoting that each intraoperative technology was cost-effective on its own. Copyright © 2016 Elsevier B.V. All rights reserved.
Biometric Analysis – A Reliable Indicator for Diagnosing Taurodontism using Panoramic Radiographs
Hegde, Veda; Anegundi, Rajesh Trayambhak; Pravinchandra, K.R.
2013-01-01
Background: Taurodontism is a clinical entity with a morpho–anatomical change in the shape of the tooth, which was thought to be absent in modern man. Taurodontism is mostly observed as an isolated trait or a component of a syndrome. Various techniques have been devised to diagnose taurodontism. Aim: The aim of this study was to analyze whether a biometric analysis was useful in diagnosing taurodontism, in radiographs which appeared to be normal on cursory observations. Setting and Design: This study was carried out in our institution by using radiographs which were taken for routine procedures. Material and Methods: In this retrospective study, panoramic radiographs were obtained from dental records of children who were aged between 9–14 years, who did not have any abnormality on cursory observations. Biometric analyses were carried out on permanent mandibular first molar(s) by using a novel biometric method. The values were tabulated and analysed. Statistics: Fischer exact probability test, Chi square test and Chi-square test with Yates correction were used for statistical analysis of the data. Results: Cursory observation did not yield us any case of taurodontism. In contrast, the biometric analysis yielded us a statistically significant number of cases of taurodontism. However, there was no statistically significant difference in the number of cases with taurodontism, which was obtained between the genders and the age group which was considered. Conclusion: Thus, taurodontism was diagnosed on a biometric analysis, which was otherwise missed on a cursory observation. It is therefore necessary from the clinical point of view, to diagnose even the mildest form of taurodontism by using metric analysis rather than just relying on a visual radiographic assessment, as its occurrence has many clinical implications and a diagnostic importance. PMID:24086912
Irani, Morvarid; Amirian, Malihe; Sadeghi, Ramin; Lez, Justine Le; Latifnejad Roudsari, Robab
2017-08-29
To evaluate the effect of folate and folate plus zinc supplementation on endocrine parameters and sperm characteristics in sub fertile men. We conducted a systematic review and meta-analysis. Electronic databases of Medline, Scopus , Google scholar and Persian databases (SID, Iran medex, Magiran, Medlib, Iran doc) were searched from 1966 to December 2016 using a set of relevant keywords including "folate or folic acid AND (infertility, infertile, sterility)".All available randomized controlled trials (RCTs), conducted on a sample of sub fertile men with semen analyses, who took oral folic acid or folate plus zinc, were included. Data collected included endocrine parameters and sperm characteristics. Statistical analyses were done by Comprehensive Meta-analysis Version 2. In total, seven studies were included. Six studies had sufficient data for meta-analysis. "Sperm concentration was statistically higher in men supplemented with folate than with placebo (P < .001)". However, folate supplementation alone did not seem to be more effective than the placebo on the morphology (P = .056) and motility of the sperms (P = .652). Folate plus zinc supplementation did not show any statistically different effect on serum testosterone (P = .86), inhibin B (P = .84), FSH (P = .054), and sperm motility (P = .169) as compared to the placebo. Yet, folate plus zinc showed statistically higher effect on the sperm concentration (P < .001), morphology (P < .001), and serum folate level (P < .001) as compared to placebo. Folate plus zinc supplementation has a positive effect on sperm characteristics in sub fertile men. However, these results should be interpreted with caution due to the important heterogeneity of the studies included in this meta-analysis. Further trials are still needed to confirm the current findings.
A new statistical method for design and analyses of component tolerance
NASA Astrophysics Data System (ADS)
Movahedi, Mohammad Mehdi; Khounsiavash, Mohsen; Otadi, Mahmood; Mosleh, Maryam
2017-03-01
Tolerancing conducted by design engineers to meet customers' needs is a prerequisite for producing high-quality products. Engineers use handbooks to conduct tolerancing. While use of statistical methods for tolerancing is not something new, engineers often use known distributions, including the normal distribution. Yet, if the statistical distribution of the given variable is unknown, a new statistical method will be employed to design tolerance. In this paper, we use generalized lambda distribution for design and analyses component tolerance. We use percentile method (PM) to estimate the distribution parameters. The findings indicated that, when the distribution of the component data is unknown, the proposed method can be used to expedite the design of component tolerance. Moreover, in the case of assembled sets, more extensive tolerance for each component with the same target performance can be utilized.
2015-08-01
the nine questions. The Statistical Package for the Social Sciences ( SPSS ) [11] was used to conduct statistical analysis on the sample. Two types...constructs. SPSS was again used to conduct statistical analysis on the sample. This time factor analysis was conducted. Factor analysis attempts to...Business Research Methods and Statistics using SPSS . P432. 11 IBM SPSS Statistics . (2012) 12 Burns, R.B., Burns, R.A. (2008) ‘Business Research
ERIC Educational Resources Information Center
Carlhed, Carina
2017-01-01
The aim of the study was to analyse enrolment patterns, and study efficiency and completion among students in programmes with professional qualifications, using microdata from Statistics Sweden. The programmes were Architecture, Medicine, Nursing, Law, Social work, Psychology, andEngineering (year 2001-2002, n = 15,918). Using the concepts from…
Bilotta, Gary S; Burnside, Niall G; Turley, Matthew D; Gray, Jeremy C; Orr, Harriet G
2017-01-01
Run-of-river (ROR) hydroelectric power (HEP) schemes are often presumed to be less ecologically damaging than large-scale storage HEP schemes. However, there is currently limited scientific evidence on their ecological impact. The aim of this article is to investigate the effects of ROR HEP schemes on communities of invertebrates in temperate streams and rivers, using a multi-site Before-After, Control-Impact (BACI) study design. The study makes use of routine environmental surveillance data collected as part of long-term national and international monitoring programmes at 22 systematically-selected ROR HEP schemes and 22 systematically-selected paired control sites. Five widely-used family-level invertebrate metrics (richness, evenness, LIFE, E-PSI, WHPT) were analysed using a linear mixed effects model. The analyses showed that there was a statistically significant effect (p<0.05) of ROR HEP construction and operation on the evenness of the invertebrate community. However, no statistically significant effects were detected on the four other metrics of community composition. The implications of these findings are discussed in this article and recommendations are made for best-practice study design for future invertebrate community impact studies.
2017-01-01
Run-of-river (ROR) hydroelectric power (HEP) schemes are often presumed to be less ecologically damaging than large-scale storage HEP schemes. However, there is currently limited scientific evidence on their ecological impact. The aim of this article is to investigate the effects of ROR HEP schemes on communities of invertebrates in temperate streams and rivers, using a multi-site Before-After, Control-Impact (BACI) study design. The study makes use of routine environmental surveillance data collected as part of long-term national and international monitoring programmes at 22 systematically-selected ROR HEP schemes and 22 systematically-selected paired control sites. Five widely-used family-level invertebrate metrics (richness, evenness, LIFE, E-PSI, WHPT) were analysed using a linear mixed effects model. The analyses showed that there was a statistically significant effect (p<0.05) of ROR HEP construction and operation on the evenness of the invertebrate community. However, no statistically significant effects were detected on the four other metrics of community composition. The implications of these findings are discussed in this article and recommendations are made for best-practice study design for future invertebrate community impact studies. PMID:28158282
Ebqa'ai, Mohammad; Ibrahim, Bashar
2017-12-01
This study aims to analyse the heavy metal pollutants in Jeddah, the second largest city in the Gulf Cooperation Council with a population exceeding 3.5 million, and many vehicles. Ninety-eight street dust samples were collected seasonally from the six major roads as well as the Jeddah Beach, and subsequently digested using modified Leeds Public Analyst method. The heavy metals (Fe, Zn, Mn, Cu, Cd, and Pb) were extracted from the ash using methyl isobutyl ketone as solvent extraction and eventually analysed by atomic absorption spectroscopy. Multivariate statistical techniques, principal component analysis (PCA), and hierarchical cluster analysis were applied to these data. Heavy metal concentrations were ranked according to the following descending order: Fe > Zn > Mn > Cu > Pb > Cd. In order to study the pollution and health risk from these heavy metals as well as estimating their effect on the environment, pollution indices, integrated pollution index, enrichment factor, daily dose average, hazard quotient, and hazard index were all analysed. The PCA showed high levels of Zn, Fe, and Cd in Al Kurnish road, while these elements were consistently detected on King Abdulaziz and Al Madina roads. The study indicates that high levels of Zn and Pb pollution were recorded for major roads in Jeddah. Six out of seven roads had high pollution indices. This study is the first step towards further investigations into current health problems in Jeddah, such as anaemia and asthma.
Statistical Literacy in the Data Science Workplace
ERIC Educational Resources Information Center
Grant, Robert
2017-01-01
Statistical literacy, the ability to understand and make use of statistical information including methods, has particular relevance in the age of data science, when complex analyses are undertaken by teams from diverse backgrounds. Not only is it essential to communicate to the consumers of information but also within the team. Writing from the…
Reporting Practices and Use of Quantitative Methods in Canadian Journal Articles in Psychology.
Counsell, Alyssa; Harlow, Lisa L
2017-05-01
With recent focus on the state of research in psychology, it is essential to assess the nature of the statistical methods and analyses used and reported by psychological researchers. To that end, we investigated the prevalence of different statistical procedures and the nature of statistical reporting practices in recent articles from the four major Canadian psychology journals. The majority of authors evaluated their research hypotheses through the use of analysis of variance (ANOVA), t -tests, and multiple regression. Multivariate approaches were less common. Null hypothesis significance testing remains a popular strategy, but the majority of authors reported a standardized or unstandardized effect size measure alongside their significance test results. Confidence intervals on effect sizes were infrequently employed. Many authors provided minimal details about their statistical analyses and less than a third of the articles presented on data complications such as missing data and violations of statistical assumptions. Strengths of and areas needing improvement for reporting quantitative results are highlighted. The paper concludes with recommendations for how researchers and reviewers can improve comprehension and transparency in statistical reporting.
Huedo-Medina, Tania B; Garcia, Marissa; Bihuniak, Jessica D; Kenny, Anne; Kerstetter, Jane
2016-03-01
Several systematic reviews/meta-analyses published within the past 10 y have examined the associations of Mediterranean-style diets (MedSDs) on cardiovascular disease (CVD) risk. However, these reviews have not been evaluated for satisfying contemporary methodologic quality standards. This study evaluated the quality of recent systematic reviews/meta-analyses on MedSD and CVD risk outcomes by using an established methodologic quality scale. The relation between review quality and impact per publication value of the journal in which the article had been published was also evaluated. To assess compliance with current standards, we applied a modified version of the Assessment of Multiple Systematic Reviews (AMSTARMedSD) quality scale to systematic reviews/meta-analyses retrieved from electronic databases that had met our selection criteria: 1) used systematic or meta-analytic procedures to review the literature, 2) examined MedSD trials, and 3) had MedSD interventions independently or combined with other interventions. Reviews completely satisfied from 8% to 75% of the AMSTARMedSD items (mean ± SD: 31.2% ± 19.4%), with those published in higher-impact journals having greater quality scores. At a minimum, 60% of the 24 reviews did not disclose full search details or apply appropriate statistical methods to combine study findings. Only 5 of the reviews included participant or study characteristics in their analyses, and none evaluated MedSD diet characteristics. These data suggest that current meta-analyses/systematic reviews evaluating the effect of MedSD on CVD risk do not fully comply with contemporary methodologic quality standards. As a result, there are more research questions to answer to enhance our understanding of how MedSD affects CVD risk or how these effects may be modified by the participant or MedSD characteristics. To clarify the associations between MedSD and CVD risk, future meta-analyses and systematic reviews should not only follow methodologic quality standards but also include more statistical modeling results when data allow. © 2016 American Society for Nutrition.
Fast and accurate imputation of summary statistics enhances evidence of functional enrichment.
Pasaniuc, Bogdan; Zaitlen, Noah; Shi, Huwenbo; Bhatia, Gaurav; Gusev, Alexander; Pickrell, Joseph; Hirschhorn, Joel; Strachan, David P; Patterson, Nick; Price, Alkes L
2014-10-15
Imputation using external reference panels (e.g. 1000 Genomes) is a widely used approach for increasing power in genome-wide association studies and meta-analysis. Existing hidden Markov models (HMM)-based imputation approaches require individual-level genotypes. Here, we develop a new method for Gaussian imputation from summary association statistics, a type of data that is becoming widely available. In simulations using 1000 Genomes (1000G) data, this method recovers 84% (54%) of the effective sample size for common (>5%) and low-frequency (1-5%) variants [increasing to 87% (60%) when summary linkage disequilibrium information is available from target samples] versus the gold standard of 89% (67%) for HMM-based imputation, which cannot be applied to summary statistics. Our approach accounts for the limited sample size of the reference panel, a crucial step to eliminate false-positive associations, and it is computationally very fast. As an empirical demonstration, we apply our method to seven case-control phenotypes from the Wellcome Trust Case Control Consortium (WTCCC) data and a study of height in the British 1958 birth cohort (1958BC). Gaussian imputation from summary statistics recovers 95% (105%) of the effective sample size (as quantified by the ratio of [Formula: see text] association statistics) compared with HMM-based imputation from individual-level genotypes at the 227 (176) published single nucleotide polymorphisms (SNPs) in the WTCCC (1958BC height) data. In addition, for publicly available summary statistics from large meta-analyses of four lipid traits, we publicly release imputed summary statistics at 1000G SNPs, which could not have been obtained using previously published methods, and demonstrate their accuracy by masking subsets of the data. We show that 1000G imputation using our approach increases the magnitude and statistical evidence of enrichment at genic versus non-genic loci for these traits, as compared with an analysis without 1000G imputation. Thus, imputation of summary statistics will be a valuable tool in future functional enrichment analyses. Publicly available software package available at http://bogdan.bioinformatics.ucla.edu/software/. bpasaniuc@mednet.ucla.edu or aprice@hsph.harvard.edu Supplementary materials are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Austin, Peter C
2007-11-01
I conducted a systematic review of the use of propensity score matching in the cardiovascular surgery literature. I examined the adequacy of reporting and whether appropriate statistical methods were used. I examined 60 articles published in the Annals of Thoracic Surgery, European Journal of Cardio-thoracic Surgery, Journal of Cardiovascular Surgery, and the Journal of Thoracic and Cardiovascular Surgery between January 1, 2004, and December 31, 2006. Thirty-one of the 60 studies did not provide adequate information on how the propensity score-matched pairs were formed. Eleven (18%) of studies did not report on whether matching on the propensity score balanced baseline characteristics between treated and untreated subjects in the matched sample. No studies used appropriate methods to compare baseline characteristics between treated and untreated subjects in the propensity score-matched sample. Eight (13%) of the 60 studies explicitly used statistical methods appropriate for the analysis of matched data when estimating the effect of treatment on the outcomes. Two studies used appropriate methods for some outcomes, but not for all outcomes. Thirty-nine (65%) studies explicitly used statistical methods that were inappropriate for matched-pairs data when estimating the effect of treatment on outcomes. Eleven studies did not report the statistical tests that were used to assess the statistical significance of the treatment effect. Analysis of propensity score-matched samples tended to be poor in the cardiovascular surgery literature. Most statistical analyses ignored the matched nature of the sample. I provide suggestions for improving the reporting and analysis of studies that use propensity score matching.
The SPARC Intercomparison of Middle Atmosphere Climatologies
NASA Technical Reports Server (NTRS)
Randel, William; Fleming, Eric; Geller, Marvin; Gelman, Mel; Hamilton, Kevin; Karoly, David; Ortland, Dave; Pawson, Steve; Swinbank, Richard; Udelhofen, Petra
2003-01-01
Our current confidence in 'observed' climatological winds and temperatures in the middle atmosphere (over altitudes approx. 10-80 km) is assessed by detailed intercomparisons of contemporary and historic data sets. These data sets include global meteorological analyses and assimilations, climatologies derived from research satellite measurements, and historical reference atmosphere circulation statistics. We also include comparisons with historical rocketsonde wind and temperature data, and with more recent lidar temperature measurements. The comparisons focus on a few basic circulation statistics, such as temperature, zonal wind, and eddy flux statistics. Special attention is focused on tropical winds and temperatures, where large differences exist among separate analyses. Assimilated data sets provide the most realistic tropical variability, but substantial differences exist among current schemes.
NASA Technical Reports Server (NTRS)
1982-01-01
A FORTRAN coded computer program and method to predict the reaction control fuel consumption statistics for a three axis stabilized rocket vehicle upper stage is described. A Monte Carlo approach is used which is more efficient by using closed form estimates of impulses. The effects of rocket motor thrust misalignment, static unbalance, aerodynamic disturbances, and deviations in trajectory, mass properties and control system characteristics are included. This routine can be applied to many types of on-off reaction controlled vehicles. The pseudorandom number generation and statistical analyses subroutines including the output histograms can be used for other Monte Carlo analyses problems.
Bradford, Williamson Z.; Fagan, Elizabeth A.; Glaspole, Ian; Glassberg, Marilyn K.; Glasscock, Kenneth F.; King, Talmadge E.; Lancaster, Lisa H.; Nathan, Steven D.; Pereira, Carlos A.; Sahn, Steven A.; Swigris, Jeffrey J.; Noble, Paul W.
2015-01-01
BACKGROUND: FVC outcomes in clinical trials on idiopathic pulmonary fibrosis (IPF) can be substantially influenced by the analytic methodology and the handling of missing data. We conducted a series of sensitivity analyses to assess the robustness of the statistical finding and the stability of the estimate of the magnitude of treatment effect on the primary end point of FVC change in a phase 3 trial evaluating pirfenidone in adults with IPF. METHODS: Source data included all 555 study participants randomized to treatment with pirfenidone or placebo in the Assessment of Pirfenidone to Confirm Efficacy and Safety in Idiopathic Pulmonary Fibrosis (ASCEND) study. Sensitivity analyses were conducted to assess whether alternative statistical tests and methods for handling missing data influenced the observed magnitude of treatment effect on the primary end point of change from baseline to week 52 in FVC. RESULTS: The distribution of FVC change at week 52 was systematically different between the two treatment groups and favored pirfenidone in each analysis. The method used to impute missing data due to death had a marked effect on the magnitude of change in FVC in both treatment groups; however, the magnitude of treatment benefit was generally consistent on a relative basis, with an approximate 50% reduction in FVC decline observed in the pirfenidone group in each analysis. CONCLUSIONS: Our results confirm the robustness of the statistical finding on the primary end point of change in FVC in the ASCEND trial and corroborate the estimated magnitude of the pirfenidone treatment effect in patients with IPF. TRIAL REGISTRY: ClinicalTrials.gov; No.: NCT01366209; URL: www.clinicaltrials.gov PMID:25856121
Dodzo, Lilian Gertrude; Mahaka, Hilda Tandazani; Mukona, Doreen; Zvinavashe, Mathilda; Haruzivishe, Clara
2017-06-01
HIV-related conditions are one of the indirect causes of maternal deaths in Zimbabwe and the prevalence rate was estimated to be 13.63% in 2009. The study utilised a descriptive correlational design on 80 pregnant women who were HIV positive at Mbuya Nehanda maternity hospital in Harare, Zimbabwe. Participants comprised a random sample of 80 postnatal mothers. Permission to carry out the study was obtained from the respective review boards. Participants signed an informed consent. Data were collected using a structured questionnaire and record review from 1 to 20 March 2012. Interviews were done in a private room and code numbers were used to identify the participants. Completed questionnaires were kept in a lockable cupboard and the researcher had sole access to them. Data were analysed using the Statistical Package for Social Sciences (SPSS) version 12. Descriptive statistics were used to analyse data on demographics, maternal health outcomes and self-care practices. Inferential statistics (Pearson's correlation and regression analysis) were used to analyse the relationship between self-care practices and maternal health outcomes. Self-care practices were good with a mean score of 8 out of 16. Majority (71.3%) fell within the good category. Maternal outcomes were poor with a mean score of 28 out of 62 and 67.5% falling in the poor category. Pearson's correlation indicated a weak significant positive relationship (r = .317, p = <.01). Regression analysis (R 2 ) was .10 implying that self-care practices explained 10% of the variance observed in maternal health outcomes. More research needs to be carried out to identify other variables affecting maternal outcomes in HIV-positive pregnant women.
Tavares, M; de Lima, C; Fernandes, W; Martinelli, V; de Lucena, M; Lima, F; Telles, A; Brandão, L; de Melo Júnior, M
2016-12-01
Inflammatory bowel disease consists of multifactorial diseases whose common manifestation is inflammation of the gastrointestinal tract and their pathogenesis remains unknown. This study aimed to analyse the gene polymorphisms in Brazilian patients with inflammatory bowel disease. A total of 101 patients diagnosed with inflammatory bowel disease were analysed for the tumour necrosis factor-alpha (-308 G/A; rs1800629) and interleukin-10 (-1082 G/A; rs1800896) gene polymorphisms. Genotyping was performed through polymerase chain reaction-sequence-specific primer, then fractionated on 2% agarose gel and visualized after staining by ethidium bromide. The anatomic-clinical form of Crohn's disease (CD) predominant was the inflammatory (32.75%), followed by fistulizing (29.31%) and 27.58% stricturing. As control group, a total of 136 healthy subjects, from the same geographical region, were enrolled. The statistical analyses were performed using R program. The frequency of the A allele at tumour necrosis factor-alpha was high in ulcerative colitis (UC) patients (51%) than in controls (22%; P > 0.01). No statistical difference was found with the genotypic and allelic frequencies of CD patients compared to controls (P = 0.54). The polymorphism -1082G/A of interleukin-10 was not statistical different between the diseases compared to controls. Tumour necrosis factor-alpha (TNF-α) (-308G/A) is associated with UC onset, suggesting that the presence of -308A allele could confer a relative risk of 3.62 more to develop UC in general population. Further studies, increasing the number of individuals, should be performed to ratify the role of TNF-α in the inflammatory bowel disease pathogenesis. © 2016 John Wiley & Sons Ltd.
Influence of family environment on language outcomes in children with myelomeningocele.
Vachha, B; Adams, R
2005-09-01
Previously, our studies demonstrated language differences impacting academic performance among children with myelomeningocele and shunted hydrocephalus (MMSH). This follow-up study considers the environmental facilitators within families (achievement orientation, intellectual-cultural orientation, active recreational orientation, independence) among a cohort of children with MMSH and their relationship to language performance. Fifty-eight monolingual, English-speaking children (36 females; mean age: 10.1 years; age range: 7-16 years) with MMSH were evaluated. Exclusionary criteria were prior shunt infection; seizure or shunt malfunction within the previous 3 months; uncorrected visual or auditory impairments; prior diagnoses of mental retardation or attention deficit disorder. The Comprehensive Assessment of Spoken Language (CASL) and the Wechsler Abbreviated Scale of Intelligence (WASI) were administered individually to all participants. The CASL Measures four subsystems: lexical, syntactic, supralinguistic and pragmatic. Parents completed the Family Environment Scale (FES) questionnaire and provided background demographic information. Spearman correlation analyses and partial correlation analyses were performed. Mean intelligence scores for the MMSH group: full scale IQ 92.2 (SD = 11.9). The CASL revealed statistically significant difficulty for supralinguistic and pragmatic (or social) language tasks. FES scores fell within the average range for the group. Spearman correlation and partial correlation analyses revealed statistically significant positive relationships for the FES 'intellectual-cultural orientation' variable and performance within the four language subsystems. Socio-economic status (SES) characteristics were analyzed and did not discriminate language performance when the intellectual-cultural orientation factor was taken into account. The role of family facilitators on language skills in children with MMSH has not previously been described. The relationship between language performance and the families' value on intellectual/cultural activities seems both statistically and intuitively sound. Focused interest in the integration of family values and practices should assist developmental specialists in supporting families and children within their most natural environment.
Kelechi, Teresa J; Mueller, Martina; Zapka, Jane G; King, Dana E
2011-11-01
The aim of this randomized clinical trial was to investigate a cryotherapy (cooling) gel wrap applied to lower leg skin affected by chronic venous disorders to determine whether therapeutic cooling improves skin microcirculation. Chronic venous disorders are under-recognized vascular health problems that result in severe skin damage and ulcerations of the lower legs. Impaired skin microcirculation contributes to venous leg ulcer development, thus new prevention therapies should address the microcirculation to prevent venous leg ulcers. Sixty participants (n = 30 per group) were randomized to receive one of two daily 30-minute interventions for four weeks. The treatment group applied the cryotherapy gel wrap around the affected lower leg skin, or compression and elevated the legs on a special pillow each evening at bedtime. The standard care group wore compression and elevated the legs only. Laboratory pre- and post-measures included microcirculation measures of skin temperature with a thermistor, blood flow with a laser Doppler flowmeter, and venous refill time with a photoplethysmograph. Data were collected between 2008 2009 and analysed using descriptive statistics, paired t-tests or Wilcoxon signed ranks tests, logistic regression analyses, and mixed model analyses. Fifty-seven participants (treatment = 28; standard care = 29) completed the study. The mean age was 62 years, 70% female, 50% African American. In the final adjusted model, there was a statistically significant decrease in blood flow between the two groups (-6.2[-11.8; -0.6], P = 0.03). No statistically significant differences were noted in temperature or venous refill time. Study findings suggest that cryotherapy improves blood flow by slowing movement within the microcirculation and thus might potentially provide a therapeutic benefit to prevent leg ulcers. © 2011 Blackwell Publishing Ltd.
Mueller, Martina; Zapka, Jane G.; King, Dana E.
2011-01-01
Aim This randomized clinical trial was conducted 2008 – 2009 to investigate a cryotherapy (cooling) gel wrap applied to lower leg skin affected by chronic venous disorders to determine whether therapeutic cooling improves skin microcirculation. Impaired skin microcirculation contributes to venous leg ulcer development, thus new prevention therapies should address the microcirculation to prevent venous leg ulcers. Data Sources Sixty participants (n = 30 per group) were randomized to receive one of two daily 30-minute interventions for four weeks. The treatment group applied the cryotherapy gel wrap around the affected lower leg skin, or compression and elevated the legs on a special pillow each evening at bedtime. The standard care group wore compression and elevated the legs only. Laboratory pre- and post-measures included microcirculation measures of skin temperature with a thermistor, blood flow with a laser Doppler flowmeter, and venous refill time with a photoplethysmograph. Review methods Data were analysed using descriptive statistics, paired t-tests or Wilcoxon signed ranks tests, logistic regression analyses, and mixed model analyses. Results Fifty-seven participants (treatment = 28; standard care = 29) completed the study. The mean age was 62 years, 70% female, 50% African American. In the final adjusted model, there was a statistically significant decrease in blood flow between the two groups (−6.2[−11.8; −0.6], P = 0.03). No statistically significant differences were noted in temperature or venous refill time. Conclusion Study findings suggest that cryotherapy improves blood flow by slowing movement within the microcirculation and thus might potentially provide a therapeutic benefit to prevent leg ulcers. PMID:21592186
Chae, Su Jin; Jeong, So Mi; Chung, Yoon-Sok
2017-09-01
This study is aimed at identifying the relationships between medical school students' academic burnout, empathy, and calling, and determining whether their calling has a mediating effect on the relationship between academic burnout and empathy. A mixed method study was conducted. One hundred twenty-seven medical students completed a survey. Scales measuring academic burnout, medical students' empathy, and calling were utilized. For statistical analysis, correlation analysis, descriptive statistics analysis, and hierarchical multiple regression analyses were conducted. For qualitative approach, eight medical students participated in a focus group interview. The study found that empathy has a statistically significant, negative correlation with academic burnout, while having a significant, positive correlation with calling. Sense of calling proved to be an effective mediator of the relationship between academic burnout and empathy. This result demonstrates that calling is a key variable that mediates the relationship between medical students' academic burnout and empathy. As such, this study provides baseline data for an education that could improve medical students' empathy skills.