'Miss Frances', 'Miss Gail' and 'Miss Sandra' Crapemyrtles

USDA-ARS?s Scientific Manuscript database

The Agricultural Research Service, United States Department of Agriculture, announces the release to nurserymen of three new crapemyrtle cultivars named 'Miss Gail', 'Miss Frances', and 'Miss Sandra'. ‘Miss Gail’ resulted from a cross-pollination between ‘Catawba’ as the female parent and ‘Arapaho’ ...

Missing data exploration: highlighting graphical presentation of missing pattern

PubMed Central

2015-01-01

Functions shipped with R base can fulfill many tasks of missing data handling. However, because the data volume of electronic medical record (EMR) system is always very large, more sophisticated methods may be helpful in data management. The article focuses on missing data handling by using advanced techniques. There are three types of missing data, that is, missing completely at random (MCAR), missing at random (MAR) and not missing at random (NMAR). This classification system depends on how missing values are generated. Two packages, Multivariate Imputation by Chained Equations (MICE) and Visualization and Imputation of Missing Values (VIM), provide sophisticated functions to explore missing data pattern. In particular, the VIM package is especially helpful in visual inspection of missing data. Finally, correlation analysis provides information on the dependence of missing data on other variables. Such information is useful in subsequent imputations. PMID:26807411

Missing data and multiple imputation in clinical epidemiological research.

PubMed

Pedersen, Alma B; Mikkelsen, Ellen M; Cronin-Fenton, Deirdre; Kristensen, Nickolaj R; Pham, Tra My; Pedersen, Lars; Petersen, Irene

2017-01-01

Missing data are ubiquitous in clinical epidemiological research. Individuals with missing data may differ from those with no missing data in terms of the outcome of interest and prognosis in general. Missing data are often categorized into the following three types: missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR). In clinical epidemiological research, missing data are seldom MCAR. Missing data can constitute considerable challenges in the analyses and interpretation of results and can potentially weaken the validity of results and conclusions. A number of methods have been developed for dealing with missing data. These include complete-case analyses, missing indicator method, single value imputation, and sensitivity analyses incorporating worst-case and best-case scenarios. If applied under the MCAR assumption, some of these methods can provide unbiased but often less precise estimates. Multiple imputation is an alternative method to deal with missing data, which accounts for the uncertainty associated with missing data. Multiple imputation is implemented in most statistical software under the MAR assumption and provides unbiased and valid estimates of associations based on information from the available data. The method affects not only the coefficient estimates for variables with missing data but also the estimates for other variables with no missing data.

Missing data and multiple imputation in clinical epidemiological research

PubMed Central

Pedersen, Alma B; Mikkelsen, Ellen M; Cronin-Fenton, Deirdre; Kristensen, Nickolaj R; Pham, Tra My; Pedersen, Lars; Petersen, Irene

2017-01-01

Missing data are ubiquitous in clinical epidemiological research. Individuals with missing data may differ from those with no missing data in terms of the outcome of interest and prognosis in general. Missing data are often categorized into the following three types: missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR). In clinical epidemiological research, missing data are seldom MCAR. Missing data can constitute considerable challenges in the analyses and interpretation of results and can potentially weaken the validity of results and conclusions. A number of methods have been developed for dealing with missing data. These include complete-case analyses, missing indicator method, single value imputation, and sensitivity analyses incorporating worst-case and best-case scenarios. If applied under the MCAR assumption, some of these methods can provide unbiased but often less precise estimates. Multiple imputation is an alternative method to deal with missing data, which accounts for the uncertainty associated with missing data. Multiple imputation is implemented in most statistical software under the MAR assumption and provides unbiased and valid estimates of associations based on information from the available data. The method affects not only the coefficient estimates for variables with missing data but also the estimates for other variables with no missing data. PMID:28352203

40 CFR 98.245 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... estimating missing data. For missing feedstock and product flow rates, use the same procedures as for missing... contents and missing molecular weights for fuels as specified in § 98.35(b)(1). For missing flare data...

Quantifying Missed Nursing Care Using the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) Survey.

PubMed

Orique, Sabrina B; Patty, Christopher M; Sandidge, Alisha; Camarena, Emma; Newsom, Rose

2017-12-01

The aim of this article is to describe the use of Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) data to measure missed nursing care and construct a missed nursing care metric. Missed nursing care varies widely within and between US hospitals. Missed nursing care can be measured utilizing the HCAHPS data. This cross-sectional study used HCAHPS data to measure missed care. This analysis includes HCAHPS data from 1125 acute care patients discharged between January 2014 and December 2014. A missed care index was computed by dividing the total number of missed care occurrences as reported by the patient into the total number of survey responses that did not indicate missed care. The computed missed care index for the organization was 0.6 with individual unit indices ranging from 0.2 to 1.4. Our methods utilize existing data to quantify missed nursing care. Based on the assessment, nursing leaders can develop interventions to decrease the incidence of missed care. Further data should be gathered to validate the incidence of missed care from HCAHPS reports.

National Geospatial-Intelligence Agency Academic Research Program

NASA Astrophysics Data System (ADS)

Loomer, S. A.

2004-12-01

"Know the Earth.Show the Way." In fulfillment of its vision, the National Geospatial-Intelligence Agency (NGA) provides geospatial intelligence in all its forms and from whatever source-imagery, imagery intelligence, and geospatial data and information-to ensure the knowledge foundation for planning, decision, and action. To achieve this, NGA conducts a multi-disciplinary program of basic research in geospatial intelligence topics through grants and fellowships to the leading investigators, research universities, and colleges of the nation. This research provides the fundamental science support to NGA's applied and advanced research programs. The major components of the NGA Academic Research Program (NARP) are: - NGA University Research Initiatives (NURI): Three-year basic research grants awarded competitively to the best investigators across the US academic community. Topics are selected to provide the scientific basis for advanced and applied research in NGA core disciplines. - Historically Black College and University - Minority Institution Research Initiatives (HBCU-MI): Two-year basic research grants awarded competitively to the best investigators at Historically Black Colleges and Universities, and Minority Institutions across the US academic community. - Director of Central Intelligence Post-Doctoral Research Fellowships: Fellowships providing access to advanced research in science and technology applicable to the intelligence community's mission. The program provides a pool of researchers to support future intelligence community needs and develops long-term relationships with researchers as they move into career positions. This paper provides information about the NGA Academic Research Program, the projects it supports and how other researchers and institutions can apply for grants under the program.

Missed nursing care and its relationship with confidence in delegation among hospital nurses.

PubMed

Saqer, Tahani J; AbuAlRub, Raeda F

2018-04-06

To (i) identify the types and reasons for missed nursing care among Jordanian hospital nurses; (ii) identify predictors of missed nursing care based on study variables; and (iii) examine the relationship between nurses' confidence in delegation and missed nursing care. Missed nursing care is a global concern for nurses and nurse administrators. Investigating the relation between the confidence in delegation and missed nursing care might help in designing strategies that enable nurses to minimise missed care and enhance quality of services. A correlational research design was used for this study. A convenience sample of 362 hospital nurses completed the missed nursing care survey, and confidence and intent to delegate scale. The results of the study revealed that ambulating and feeding patients on time, doing mouth care and attending interdisciplinary care conferences were the most frequent types of missed care. The mean score for missed nursing care was (2.78) on a scale from 1-5. The most prevalent reasons for missed care were "labour resources, followed by material resources, and then communication". Around 45% of the variation in the perceived level of "missed nursing care" was explained by background variables and perceived reasons for missed nursing. However, the relationship between confidence in delegation and missed care was insignificant. The results of this study add to the body of international literature on most prevalent types and reasons for missed nursing care in a different cultural context. Highlighting most prevalent reasons for missed nursing care could help nurse administrators in designing responsive strategies to eliminate or reduces such reasons. © 2018 John Wiley & Sons Ltd.

A Simulation Study of Missing Data with Multiple Missing X's

ERIC Educational Resources Information Center

Rubright, Jonathan D.; Nandakumar, Ratna; Glutting, Joseph J.

2014-01-01

When exploring missing data techniques in a realistic scenario, the current literature is limited: most studies only consider consequences with data missing on a single variable. This simulation study compares the relative bias of two commonly used missing data techniques when data are missing on more than one variable. Factors varied include type…

Principled Missing Data Treatments.

PubMed

Lang, Kyle M; Little, Todd D

2018-04-01

We review a number of issues regarding missing data treatments for intervention and prevention researchers. Many of the common missing data practices in prevention research are still, unfortunately, ill-advised (e.g., use of listwise and pairwise deletion, insufficient use of auxiliary variables). Our goal is to promote better practice in the handling of missing data. We review the current state of missing data methodology and recent missing data reporting in prevention research. We describe antiquated, ad hoc missing data treatments and discuss their limitations. We discuss two modern, principled missing data treatments: multiple imputation and full information maximum likelihood, and we offer practical tips on how to best employ these methods in prevention research. The principled missing data treatments that we discuss are couched in terms of how they improve causal and statistical inference in the prevention sciences. Our recommendations are firmly grounded in missing data theory and well-validated statistical principles for handling the missing data issues that are ubiquitous in biosocial and prevention research. We augment our broad survey of missing data analysis with references to more exhaustive resources.

Analysis of Longitudinal Outcome Data with Missing Values in Total Knee Arthroplasty.

PubMed

Kang, Yeon Gwi; Lee, Jang Taek; Kang, Jong Yeal; Kim, Ga Hye; Kim, Tae Kyun

2016-01-01

We sought to determine the influence of missing data on the statistical results, and to determine which statistical method is most appropriate for the analysis of longitudinal outcome data of TKA with missing values among repeated measures ANOVA, generalized estimating equation (GEE) and mixed effects model repeated measures (MMRM). Data sets with missing values were generated with different proportion of missing data, sample size and missing-data generation mechanism. Each data set was analyzed with three statistical methods. The influence of missing data was greater with higher proportion of missing data and smaller sample size. MMRM tended to show least changes in the statistics. When missing values were generated by 'missing not at random' mechanism, no statistical methods could fully avoid deviations in the results. Copyright © 2016 Elsevier Inc. All rights reserved.

Patient understanding of oral contraceptive pill instructions related to missed pills: a systematic review.

PubMed

Zapata, Lauren B; Steenland, Maria W; Brahmi, Dalia; Marchbanks, Polly A; Curtis, Kathryn M

2013-05-01

Instructions on what to do after pills are missed are critical to reducing unintended pregnancies resulting from patient non-adherence to oral contraceptive (OC) regimens. Missed pill instructions have previously been criticized for being too complex, lacking a definition of what is meant by "missed pills," and for being confusing to women who may not know the estrogen content of their formulation. To help inform the development of missed pill guidance to be included in the forthcoming US Selected Practice Recommendations, the objective of this systematic review was to evaluate the evidence on patient understanding of missed pill instructions. We searched the PubMed database for peer-reviewed articles that examined patient understanding of OC pill instructions that were published in any language from inception of the database through March 2012. We included studies that examined women's knowledge and understanding of missed pill instructions after exposure to some written material (e.g., patient package insert, brochure), as well as studies that compared different types of missed pill instructions on women's comprehension. We used standard abstract forms and grading systems to summarize and assess the quality of the evidence. From 1620 articles, nine studies met our inclusion criteria. Evidence from one randomized controlled trial (RCT) and two descriptive studies found that more women knew what to do after missing 1 pill than after missing 2 or 3 pills (Level I, good, to Level II-3, poor), and two descriptive studies found that more women knew what to do after missing 2 pills than after missing 3 pills (Level II-3, fair). Data from two descriptive studies documented the difficulty women have understanding missed pill instructions contained in patient package inserts (Level II-3, poor), and evidence from two RCTs found that providing written brochures with information on missed pill instructions in addition to contraceptive counseling significantly improved knowledge of how to manage missed pills for up to three months compared to contraceptive counseling alone (Level I, fair). Evidence from one RCT found that graphic-based missed pill instructions were better than text-only instructions (Level I, good), and data from two RCTs found that less information resulted in improved comprehension (Level I, good to fair). Evidence from one descriptive study found that many women missing pills did not intend to follow recommended actions per missed pill instructions despite understanding the guidance (Level II-3, poor). There is wide variability in the percent of women having correct knowledge on what to do when pills are missed after exposure to written missed pills instructions, with more women knowing what to do after missing 1 pill than after missing 2 or 3 pills. Women have difficulty understanding missed pill instructions contained in patient package inserts. Providing written brochures with information on missed pill instructions in addition to contraceptive counseling may improve knowledge of how to manage missed pills. Graphic-based missed pill instructions and those containing less information may result in improved comprehension. Even with clear instructions, many women missing pills may choose not to follow the recommended actions. Published by Elsevier Inc.

Patterns of missing data in the use of the endometriosis symptom diary.

PubMed

Seitz, Christian; Lanius, Vivian; Lippert, Susanne; Gerlinger, Christoph; Haberland, Claudia; Oehmke, Frank; Tinneberg, Hans-Rudolf

2018-06-08

Endometriosis is a common, chronic condition in women of reproductive age that is characterized by the presence of functional endometriotic lesions outside the uterus. The Endometriosis Symptom Diary (ESD) is an electronic patient-reported outcome (ePRO) instrument that assesses women's experience of endometriosis symptoms, with pain scored using a 0-10 numeric rating scale. This study investigated patterns of data missing from the ESD in the VALEPRO study. Post hoc analyses of missing data were conducted. Of 272 participants using the ESD, 26.5% had no missing diary entries, 46.7% had > 0-5% of entries missing, 13.2% had > 5-10% of entries missing and 13.6% had > 10% of entries missing over the entire study period. The duration of missing episodes (defined as ≥1 consecutive days with missing diary entries) was generally short; most (81.4%) were 1 day. The difference in mean worst pain scores between missing and complete episodes per participant was - 0.1, suggesting that missing episodes were not related to severity of pain. Entries were significantly more likely to be missing on Fridays (18.5%) and Saturdays (22.9%) compared with other days of the week (p < 0.0001). Participants in the USA had significantly more long missing episodes than those in Germany (proportions of missing episodes longer than 1 day, 22.6 and 10.5%, respectively; p < 0.0001). The proportions of women with ≥1 missing entry were 50.0, 70.2 and 79.8% for women with elementary education, secondary education, and a college or university education, respectively. The proportions of women with ≥1 missing entry were similar for those with and without children (72.2 and 74.3%, respectively). Most participants were highly compliant with entering data in the ESD and the amount of missing data was low. Entries were significantly more likely to be missing on Fridays and Saturdays compared with other days of the week, and participants in the USA had significantly more long missing episodes than participants in Germany. Clinicaltrials.gov, NCT01643122 , registered 4 July 2012.

Missed doses of oral antihyperglycemic medications in US adults with type 2 diabetes mellitus: prevalence and self-reported reasons.

PubMed

Vietri, Jeffrey T; Wlodarczyk, Catherine S; Lorenzo, Rose; Rajpathak, Swapnil

2016-09-01

Adherence to antihyperglycemic medication is thought to be suboptimal, but the proportion of patients missing doses, the number of doses missed, and reasons for missing are not well described. This survey was conducted to estimate the prevalence of and reasons for missed doses of oral antihyperglycemic medications among US adults with type 2 diabetes mellitus, and to explore associations between missed doses and health outcomes. The study was a cross-sectional patient survey. Respondents were contacted via a commercial survey panel and completed an on-line questionnaire via the Internet. Respondents provided information about their use of oral antihyperglycemic medications including doses missed in the prior 4 weeks, personal characteristics, and health outcomes. Weights were calculated to project the prevalence to the US adult population with type 2 diabetes mellitus. Outcomes were compared according to number of doses missed in the past 4 weeks using bivariate statistics and generalized linear models. Approximately 30% of adult patients with type 2 diabetes mellitus reported missing or reducing ≥1 dose of oral antihyperglycemic medication in the prior 4 weeks. Accidental missing was more commonly reported than purposeful skipping, with forgetting the most commonly reported reason. The timing of missed doses suggested respondents had also forgotten about doses missed, so the prevalence of missed doses is likely higher than reported. Outcomes were poorer among those who reported missing three or more doses in the prior 4 weeks. A substantial number of US adults with type 2 diabetes mellitus miss doses of their oral antihyperglycemic medications.

Empirical likelihood method for non-ignorable missing data problems.

PubMed

Guan, Zhong; Qin, Jing

2017-01-01

Missing response problem is ubiquitous in survey sampling, medical, social science and epidemiology studies. It is well known that non-ignorable missing is the most difficult missing data problem where the missing of a response depends on its own value. In statistical literature, unlike the ignorable missing data problem, not many papers on non-ignorable missing data are available except for the full parametric model based approach. In this paper we study a semiparametric model for non-ignorable missing data in which the missing probability is known up to some parameters, but the underlying distributions are not specified. By employing Owen (1988)'s empirical likelihood method we can obtain the constrained maximum empirical likelihood estimators of the parameters in the missing probability and the mean response which are shown to be asymptotically normal. Moreover the likelihood ratio statistic can be used to test whether the missing of the responses is non-ignorable or completely at random. The theoretical results are confirmed by a simulation study. As an illustration, the analysis of a real AIDS trial data shows that the missing of CD4 counts around two years are non-ignorable and the sample mean based on observed data only is biased.

Epoxying Isoprene Chemistry

EPA Science Inventory

It seems that every few months we read about another missing aspect of atmospheric chemistry: missing products, missing reactivity, missing sources, missing understanding. Thus, it is with some relief that we read in this issue the paper of Paulot et al. The paper provides more...

Prevalence and Correlates of Missing Meals Among High School Students-United States, 2010.

PubMed

Demissie, Zewditu; Eaton, Danice K; Lowry, Richard; Nihiser, Allison J; Foltz, Jennifer L

2018-01-01

To determine the prevalence and correlates of missing meals among adolescents. The 2010 National Youth Physical Activity and Nutrition Study, a cross-sectional study. School based. A nationally representative sample of 11 429 high school students. Breakfast, lunch, and dinner consumption; demographics; measured and perceived weight status; physical activity and sedentary behaviors; and fruit, vegetable, milk, sugar-sweetened beverage, and fast-food intake. Prevalence estimates for missing breakfast, lunch, or dinner on ≥1 day during the past 7 days were calculated. Associations between demographics and missing meals were tested. Associations of lifestyle and dietary behaviors with missing meals were examined using logistic regression controlling for sex, race/ethnicity, and grade. In 2010, 63.1% of students missed breakfast, 38.2% missed lunch, and 23.3% missed dinner; the prevalence was highest among female and non-Hispanic black students. Being overweight/obese, perceiving oneself to be overweight, and video game/computer use were associated with increased risk of missing meals. Physical activity behaviors were associated with reduced risk of missing meals. Students who missed breakfast were less likely to eat fruits and vegetables and more likely to consume sugar-sweetened beverages and fast food. Breakfast was the most frequently missed meal, and missing breakfast was associated with the greatest number of less healthy dietary practices. Intervention and education efforts might prioritize breakfast consumption.

Is Spending More Time Associated With Less Missed Care?: A Comparison of Time Use and Missed Care Across 15 Nursing Units at 2 Hospitals.

PubMed

McNair, Norma; Baird, Jennifer; Grogan, Tristan R; Walsh, Catherine M; Liang, Li-Jung; Worobel-Luk, Pamela; Needleman, Jack; Nuckols, Teryl K

2016-09-01

The aim of this study is to examine the relationship between nursing time use and perceptions of missed care. Recent literature has highlighted the problem of missed nursing care, but little is known about how nurses' time use patterns are associated with reports of missed care. In 15 nursing units at 2 hospitals, we assessed registered nurse (RN) perceptions of missed care, observed time use by RNs, and examined the relationship between time spent and degree of missed care at the nursing unit level. Patterns of time use were similar across hospitals, with 25% of time spent on documentation. For 6 different categories of nursing tasks, no association was detected between time use, including time spent on documentation, and the degree of missed care at the nursing unit level. Nursing time use cannot fully explain variation in missed care across nursing units. Further work is needed to account for patterns of missed care.

When and how should multiple imputation be used for handling missing data in randomised clinical trials - a practical guide with flowcharts.

PubMed

Jakobsen, Janus Christian; Gluud, Christian; Wetterslev, Jørn; Winkel, Per

2017-12-06

Missing data may seriously compromise inferences from randomised clinical trials, especially if missing data are not handled appropriately. The potential bias due to missing data depends on the mechanism causing the data to be missing, and the analytical methods applied to amend the missingness. Therefore, the analysis of trial data with missing values requires careful planning and attention. The authors had several meetings and discussions considering optimal ways of handling missing data to minimise the bias potential. We also searched PubMed (key words: missing data; randomi*; statistical analysis) and reference lists of known studies for papers (theoretical papers; empirical studies; simulation studies; etc.) on how to deal with missing data when analysing randomised clinical trials. Handling missing data is an important, yet difficult and complex task when analysing results of randomised clinical trials. We consider how to optimise the handling of missing data during the planning stage of a randomised clinical trial and recommend analytical approaches which may prevent bias caused by unavoidable missing data. We consider the strengths and limitations of using of best-worst and worst-best sensitivity analyses, multiple imputation, and full information maximum likelihood. We also present practical flowcharts on how to deal with missing data and an overview of the steps that always need to be considered during the analysis stage of a trial. We present a practical guide and flowcharts describing when and how multiple imputation should be used to handle missing data in randomised clinical.

40 CFR 75.37 - Missing data procedures for moisture.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 17 2012-07-01 2012-07-01 false Missing data procedures for moisture... PROGRAMS (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.37 Missing... system shall substitute for missing moisture data using the procedures of this section. (b) Where no...

40 CFR 75.37 - Missing data procedures for moisture.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 16 2010-07-01 2010-07-01 false Missing data procedures for moisture... PROGRAMS (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.37 Missing... system shall substitute for missing moisture data using the procedures of this section. (b) Where no...

Treatment of Missing Data in Workforce Education Research

ERIC Educational Resources Information Center

Gemici, Sinan; Rojewski, Jay W.; Lee, In Heok

2012-01-01

Most quantitative analyses in workforce education are affected by missing data. Traditional approaches to remedy missing data problems often result in reduced statistical power and biased parameter estimates due to systematic differences between missing and observed values. This article examines the treatment of missing data in pertinent…

40 CFR 75.37 - Missing data procedures for moisture.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 17 2014-07-01 2014-07-01 false Missing data procedures for moisture... PROGRAMS (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.37 Missing... system shall substitute for missing moisture data using the procedures of this section. (b) Where no...

40 CFR 75.37 - Missing data procedures for moisture.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 17 2013-07-01 2013-07-01 false Missing data procedures for moisture... PROGRAMS (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.37 Missing... system shall substitute for missing moisture data using the procedures of this section. (b) Where no...

40 CFR 75.37 - Missing data procedures for moisture.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 16 2011-07-01 2011-07-01 false Missing data procedures for moisture... PROGRAMS (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.37 Missing... system shall substitute for missing moisture data using the procedures of this section. (b) Where no...

5 CFR 880.203 - Missing annuitant status and suspension of annuity.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 5 Administrative Personnel 2 2010-01-01 2010-01-01 false Missing annuitant status and suspension... UNEXPLAINED ABSENCE Procedures § 880.203 Missing annuitant status and suspension of annuity. (a) Upon receipt... status of missing annuitant. The Associate Director will then— (1) Suspend payments to the missing...

5 CFR 880.203 - Missing annuitant status and suspension of annuity.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 5 Administrative Personnel 2 2012-01-01 2012-01-01 false Missing annuitant status and suspension... UNEXPLAINED ABSENCE Procedures § 880.203 Missing annuitant status and suspension of annuity. (a) Upon receipt... status of missing annuitant. The Associate Director will then— (1) Suspend payments to the missing...

29 CFR 4050.7 - Benefits of missing participants-in general.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 29 Labor 9 2014-07-01 2014-07-01 false Benefits of missing participants-in general. 4050.7 Section... TERMINATIONS MISSING PARTICIPANTS § 4050.7 Benefits of missing participants—in general. (a) If annuity purchased. If a plan administrator distributes a missing participant's benefit by purchasing an irrevocable...

29 CFR 4050.3 - Method of distribution for missing participants.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 29 Labor 9 2013-07-01 2013-07-01 false Method of distribution for missing participants. 4050.3... TERMINATIONS MISSING PARTICIPANTS § 4050.3 Method of distribution for missing participants. The plan administrator of a terminating plan must distribute benefits for each missing participant by— (a) Purchasing...

38 CFR 1.705 - Restrictions on use of missing children information.

Code of Federal Regulations, 2011 CFR

2011-07-01

... missing children information. 1.705 Section 1.705 Pensions, Bonuses, and Veterans' Relief DEPARTMENT OF VETERANS AFFAIRS GENERAL PROVISIONS Use of Official Mail in the Location and Recovery of Missing Children § 1.705 Restrictions on use of missing children information. Missing children pictures and...

38 CFR 1.705 - Restrictions on use of missing children information.

Code of Federal Regulations, 2013 CFR

2013-07-01

... missing children information. 1.705 Section 1.705 Pensions, Bonuses, and Veterans' Relief DEPARTMENT OF VETERANS AFFAIRS GENERAL PROVISIONS Use of Official Mail in the Location and Recovery of Missing Children § 1.705 Restrictions on use of missing children information. Missing children pictures and...

29 CFR 4050.7 - Benefits of missing participants-in general.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 29 Labor 9 2011-07-01 2011-07-01 false Benefits of missing participants-in general. 4050.7 Section... TERMINATIONS MISSING PARTICIPANTS § 4050.7 Benefits of missing participants—in general. (a) If annuity purchased. If a plan administrator distributes a missing participant's benefit by purchasing an irrevocable...

38 CFR 1.705 - Restrictions on use of missing children information.

Code of Federal Regulations, 2010 CFR

2010-07-01

... missing children information. 1.705 Section 1.705 Pensions, Bonuses, and Veterans' Relief DEPARTMENT OF VETERANS AFFAIRS GENERAL PROVISIONS Use of Official Mail in the Location and Recovery of Missing Children § 1.705 Restrictions on use of missing children information. Missing children pictures and...

29 CFR 4050.9 - Annuity or elective lump sum-living missing participant.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 29 Labor 9 2014-07-01 2014-07-01 false Annuity or elective lump sum-living missing participant... CORPORATION PLAN TERMINATIONS MISSING PARTICIPANTS § 4050.9 Annuity or elective lump sum—living missing participant. This section applies to a missing participant whose designated benefit was determined under...

29 CFR 4050.3 - Method of distribution for missing participants.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 29 Labor 9 2012-07-01 2012-07-01 false Method of distribution for missing participants. 4050.3... TERMINATIONS MISSING PARTICIPANTS § 4050.3 Method of distribution for missing participants. The plan administrator of a terminating plan must distribute benefits for each missing participant by— (a) Purchasing...

29 CFR 4050.9 - Annuity or elective lump sum-living missing participant.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 29 Labor 9 2011-07-01 2011-07-01 false Annuity or elective lump sum-living missing participant... CORPORATION PLAN TERMINATIONS MISSING PARTICIPANTS § 4050.9 Annuity or elective lump sum—living missing participant. This section applies to a missing participant whose designated benefit was determined under...

29 CFR 4050.7 - Benefits of missing participants-in general.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 29 Labor 9 2010-07-01 2010-07-01 false Benefits of missing participants-in general. 4050.7 Section... TERMINATIONS MISSING PARTICIPANTS § 4050.7 Benefits of missing participants—in general. (a) If annuity purchased. If a plan administrator distributes a missing participant's benefit by purchasing an irrevocable...

29 CFR 4050.9 - Annuity or elective lump sum-living missing participant.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 29 Labor 9 2013-07-01 2013-07-01 false Annuity or elective lump sum-living missing participant... CORPORATION PLAN TERMINATIONS MISSING PARTICIPANTS § 4050.9 Annuity or elective lump sum—living missing participant. This section applies to a missing participant whose designated benefit was determined under...

29 CFR 4050.7 - Benefits of missing participants-in general.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 29 Labor 9 2013-07-01 2013-07-01 false Benefits of missing participants-in general. 4050.7 Section... TERMINATIONS MISSING PARTICIPANTS § 4050.7 Benefits of missing participants—in general. (a) If annuity purchased. If a plan administrator distributes a missing participant's benefit by purchasing an irrevocable...

29 CFR 4050.3 - Method of distribution for missing participants.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 29 Labor 9 2014-07-01 2014-07-01 false Method of distribution for missing participants. 4050.3... TERMINATIONS MISSING PARTICIPANTS § 4050.3 Method of distribution for missing participants. The plan administrator of a terminating plan must distribute benefits for each missing participant by— (a) Purchasing...

5 CFR 880.203 - Missing annuitant status and suspension of annuity.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 5 Administrative Personnel 2 2011-01-01 2011-01-01 false Missing annuitant status and suspension... UNEXPLAINED ABSENCE Procedures § 880.203 Missing annuitant status and suspension of annuity. (a) Upon receipt... status of missing annuitant. The Associate Director will then— (1) Suspend payments to the missing...

38 CFR 1.705 - Restrictions on use of missing children information.

Code of Federal Regulations, 2012 CFR

2012-07-01

... missing children information. 1.705 Section 1.705 Pensions, Bonuses, and Veterans' Relief DEPARTMENT OF VETERANS AFFAIRS GENERAL PROVISIONS Use of Official Mail in the Location and Recovery of Missing Children § 1.705 Restrictions on use of missing children information. Missing children pictures and...

29 CFR 4050.3 - Method of distribution for missing participants.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 29 Labor 9 2010-07-01 2010-07-01 false Method of distribution for missing participants. 4050.3... TERMINATIONS MISSING PARTICIPANTS § 4050.3 Method of distribution for missing participants. The plan administrator of a terminating plan must distribute benefits for each missing participant by— (a) Purchasing...

5 CFR 880.203 - Missing annuitant status and suspension of annuity.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 5 Administrative Personnel 2 2013-01-01 2013-01-01 false Missing annuitant status and suspension... UNEXPLAINED ABSENCE Procedures § 880.203 Missing annuitant status and suspension of annuity. (a) Upon receipt... status of missing annuitant. The Associate Director will then— (1) Suspend payments to the missing...

5 CFR 880.203 - Missing annuitant status and suspension of annuity.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 5 Administrative Personnel 2 2014-01-01 2014-01-01 false Missing annuitant status and suspension... UNEXPLAINED ABSENCE Procedures § 880.203 Missing annuitant status and suspension of annuity. (a) Upon receipt... status of missing annuitant. The Associate Director will then— (1) Suspend payments to the missing...

29 CFR 4050.7 - Benefits of missing participants-in general.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 29 Labor 9 2012-07-01 2012-07-01 false Benefits of missing participants-in general. 4050.7 Section... TERMINATIONS MISSING PARTICIPANTS § 4050.7 Benefits of missing participants—in general. (a) If annuity purchased. If a plan administrator distributes a missing participant's benefit by purchasing an irrevocable...

29 CFR 4050.9 - Annuity or elective lump sum-living missing participant.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 29 Labor 9 2012-07-01 2012-07-01 false Annuity or elective lump sum-living missing participant... CORPORATION PLAN TERMINATIONS MISSING PARTICIPANTS § 4050.9 Annuity or elective lump sum—living missing participant. This section applies to a missing participant whose designated benefit was determined under...

38 CFR 1.705 - Restrictions on use of missing children information.

Code of Federal Regulations, 2014 CFR

2014-07-01

... missing children information. 1.705 Section 1.705 Pensions, Bonuses, and Veterans' Relief DEPARTMENT OF VETERANS AFFAIRS GENERAL PROVISIONS Use of Official Mail in the Location and Recovery of Missing Children § 1.705 Restrictions on use of missing children information. Missing children pictures and...

29 CFR 4050.3 - Method of distribution for missing participants.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 29 Labor 9 2011-07-01 2011-07-01 false Method of distribution for missing participants. 4050.3... TERMINATIONS MISSING PARTICIPANTS § 4050.3 Method of distribution for missing participants. The plan administrator of a terminating plan must distribute benefits for each missing participant by— (a) Purchasing...

40 CFR 75.31 - Initial missing data procedures.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 16 2010-07-01 2010-07-01 false Initial missing data procedures. 75.31... (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.31 Initial missing data.... For each hour of missing SO2, Hg, or CO2 emissions concentration data (including CO2 data converted...

40 CFR 75.31 - Initial missing data procedures.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 16 2011-07-01 2011-07-01 false Initial missing data procedures. 75.31... (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.31 Initial missing data..., or O2 concentration data, and moisture data. For each hour of missing SO2 or CO2 emissions...

40 CFR 98.265 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... estimating missing data. (a) For each missing value of the inorganic carbon content of phosphate rock or... immediately preceding and immediately following the missing data incident. You must document and keep records...

40 CFR 75.35 - Missing data procedures for CO2.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 16 2011-07-01 2011-07-01 false Missing data procedures for CO2. 75.35... (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.35 Missing data... the 720 quality-assured monitor operating hours preceding implementation of the standard missing data...

40 CFR 75.35 - Missing data procedures for CO2.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 16 2010-07-01 2010-07-01 false Missing data procedures for CO2. 75.35... (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.35 Missing data... the 720 quality-assured monitor operating hours preceding implementation of the standard missing data...

40 CFR 75.35 - Missing data procedures for CO 2.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 17 2013-07-01 2013-07-01 false Missing data procedures for CO 2. 75... (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.35 Missing data... the 720 quality-assured monitor operating hours preceding implementation of the standard missing data...

40 CFR 75.35 - Missing data procedures for CO2.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 17 2012-07-01 2012-07-01 false Missing data procedures for CO2. 75.35... (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.35 Missing data... the 720 quality-assured monitor operating hours preceding implementation of the standard missing data...

40 CFR 75.31 - Initial missing data procedures.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 17 2013-07-01 2013-07-01 false Initial missing data procedures. 75.31... (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.31 Initial missing data..., or O2 concentration data, and moisture data. For each hour of missing SO2 or CO2 emissions...

40 CFR 75.31 - Initial missing data procedures.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 17 2012-07-01 2012-07-01 false Initial missing data procedures. 75.31... (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.31 Initial missing data..., or O2 concentration data, and moisture data. For each hour of missing SO2 or CO2 emissions...

40 CFR 75.31 - Initial missing data procedures.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 17 2014-07-01 2014-07-01 false Initial missing data procedures. 75.31... (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.31 Initial missing data..., or O2 concentration data, and moisture data. For each hour of missing SO2 or CO2 emissions...

40 CFR 98.265 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... estimating missing data. (a) For each missing value of the inorganic carbon content of phosphate rock or... immediately preceding and immediately following the missing data incident. You must document and keep records...

40 CFR 98.265 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... estimating missing data. (a) For each missing value of the inorganic carbon content of phosphate rock or... immediately preceding and immediately following the missing data incident. You must document and keep records...

40 CFR 75.35 - Missing data procedures for CO 2.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 17 2014-07-01 2014-07-01 false Missing data procedures for CO 2. 75... (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.35 Missing data... the 720 quality-assured monitor operating hours preceding implementation of the standard missing data...

An Overview on Missing Children. Hearing before the Subcommittee on Children, Family, Drugs and Alcoholism of the Committee on Labor and Human Resources. United States Senate, Ninety-Ninth Congress, First Session on Review of Progress Made on the Plight of Missing Children, and the Involvement of Businesses, Corporations, and Organizations in the Search for Missing Children.

ERIC Educational Resources Information Center

Congress of the U.S., Washington, DC. Senate Committee on Labor and Human Resources.

This document is the text of a Congressional hearing on the plight of missing children. Chairman Paula Hawkins' opening remarks discuss the provisions of the Missing Children Act of 1982 and its success, the Missing Children's Assistance Act of 1984 authorizing the National Center for Missing and Exploited Children, and the continuing need to…

[Prevention and handling of missing data in clinical trials].

PubMed

Jiang, Zhi-wei; Li, Chan-juan; Wang, Ling; Xia, Jie-lai

2015-11-01

Missing data is a common but unavoidable issue in clinical trials. It not only lowers the trial power, but brings the bias to the trial results. Therefore, on one hand, the missing data handling methods are employed in data analysis. On the other hand, it is vital to prevent the missing data in the trials. Prevention of missing data should take the first place. From the perspective of data, firstly, some measures should be taken at the stages of protocol design, data collection and data check to enhance the patients' compliance and reduce the unnecessary missing data. Secondly, the causes of confirmed missing data in the trials should be notified and recorded in detail, which are very important to determine the mechanism of missing data and choose the suitable missing data handling methods, e.g., last observation carried forward (LOCF); multiple imputation (MI); mixed-effect model repeated measure (MMRM), etc.

Mind the Gap: The Prospects of Missing Data.

PubMed

McConnell, Meghan; Sherbino, Jonathan; Chan, Teresa M

2016-12-01

The increasing use of workplace-based assessments (WBAs) in competency-based medical education has led to large data sets that assess resident performance longitudinally. With large data sets, problems that arise from missing data are increasingly likely. The purpose of this study is to examine (1) whether data are missing at random across various WBAs, and (2) the relationship between resident performance and the proportion of missing data. During 2012-2013, a total of 844 WBAs of CanMEDs Roles were completed for 9 second-year emergency medicine residents. To identify whether missing data were randomly distributed across various WBAs, the total number of missing data points was calculated for each Role. To examine whether the amount of missing data was related to resident performance, 5 faculty members rank-ordered the residents based on performance. A median rank score was calculated for each resident and was correlated with the proportion of missing data. More data were missing for Health Advocate and Professional WBAs relative to other competencies ( P  < .001). Furthermore, resident rankings were not related to the proportion of missing data points ( r  = 0.29, P  > .05). The results of the present study illustrate that some CanMEDS Roles are less likely to be assessed than others. At the same time, the amount of missing data did not correlate with resident performance, suggesting lower-performing residents are no more likely to have missing data than their higher-performing peers. This article discusses several approaches to dealing with missing data.

The Candy Crush Sweet Tooth: How 'Near-misses' in Candy Crush Increase Frustration, and the Urge to Continue Gameplay.

PubMed

Larche, Chanel J; Musielak, Natalia; Dixon, Mike J

2017-06-01

Like many gambling games, the exceedingly popular and lucrative smartphone game "Candy Crush" features near-miss outcomes. In slot machines, a near-miss involves getting two of the needed three high-paying symbols on the pay-line (i.e., just missing the big win). In Candy Crush, the game signals when you just miss getting to the next level by one or two moves. Because near-misses in gambling games have consistently been shown to invigorate play despite being frustrating outcomes, the goal of the present study was to examine whether such near-misses trigger increases in player arousal, frustration and urge to continue play in Candy Crush. Sixty avid Candy Crush players were recruited to play the game for 30 min while having their Heart Rate, Skin Conductance Level, subjective arousal, frustration and urge to play recorded for three types of outcomes: wins (where they level up), losses (where they don't come close to levelling up), and near-misses (where they just miss levelling up). Near-misses were more arousing than losses as indexed by increased heart rate and greater subjective arousal. Near-misses were also subjectively rated as the most frustrating of all outcomes. Most importantly, of any type of outcome, near-misses triggered the most substantial urge to continue play. These findings suggest that near-misses in Candy Crush play a role in player commitment to the game, and may contribute to players playing longer than intended.

Testing of NASA LaRC Materials under MISSE 6 and MISSE 7 Missions

NASA Technical Reports Server (NTRS)

Prasad, Narasimha S.

2009-01-01

The objective of the Materials International Space Station Experiment (MISSE) is to study the performance of novel materials when subjected to the synergistic effects of the harsh space environment for several months. MISSE missions provide an opportunity for developing space qualifiable materials. Two lasers and a few optical components from NASA Langley Research Center (LaRC) were included in the MISSE 6 mission for long term exposure. MISSE 6 items were characterized and packed inside a ruggedized Passive Experiment Container (PEC) that resembles a suitcase. The PEC was tested for survivability due to launch conditions. MISSE 6 was transported to the international Space Station (ISS) via STS 123 on March 11. 2008. The astronauts successfully attached the PEC to external handrails of the ISS and opened the PEC for long term exposure to the space environment. The current plan is to bring the MISSE 6 PEC back to the Earth via STS 128 mission scheduled for launch in August 2009. Currently, preparations for launching the MISSE 7 mission are progressing. Laser and lidar components assembled on a flight-worthy platform are included from NASA LaRC. MISSE 7 launch is scheduled to be launched on STS 129 mission. This paper will briefly review recent efforts on MISSE 6 and MISSE 7 missions at NASA Langley Research Center (LaRC).

20 CFR 364.3 - Publication of missing children information in the Railroad Retirement Board's in-house...

Code of Federal Regulations, 2013 CFR

2013-04-01

... 20 Employees' Benefits 1 2013-04-01 2012-04-01 true Publication of missing children information in... THE LOCATION AND RECOVERY OF MISSING CHILDREN § 364.3 Publication of missing children information in the Railroad Retirement Board's in-house publications. (a) All-A-Board. Information about missing...

20 CFR 364.3 - Publication of missing children information in the Railroad Retirement Board's in-house...

Code of Federal Regulations, 2014 CFR

2014-04-01

... 20 Employees' Benefits 1 2014-04-01 2012-04-01 true Publication of missing children information in... THE LOCATION AND RECOVERY OF MISSING CHILDREN § 364.3 Publication of missing children information in the Railroad Retirement Board's in-house publications. (a) All-A-Board. Information about missing...

20 CFR 364.3 - Publication of missing children information in the Railroad Retirement Board's in-house...

Code of Federal Regulations, 2012 CFR

2012-04-01

... 20 Employees' Benefits 1 2012-04-01 2012-04-01 false Publication of missing children information... THE LOCATION AND RECOVERY OF MISSING CHILDREN § 364.3 Publication of missing children information in the Railroad Retirement Board's in-house publications. (a) All-A-Board. Information about missing...

28 CFR 19.2 - Contact person for Missing Children Penalty Mail Program.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 28 Judicial Administration 1 2010-07-01 2010-07-01 false Contact person for Missing Children... IN THE LOCATION AND RECOVERY OF MISSING CHILDREN § 19.2 Contact person for Missing Children Penalty Mail Program. The DOJ contact person for the Missing Children Penalty Mail Program is: Patricia...

28 CFR 19.2 - Contact person for Missing Children Penalty Mail Program.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 28 Judicial Administration 1 2013-07-01 2013-07-01 false Contact person for Missing Children... IN THE LOCATION AND RECOVERY OF MISSING CHILDREN § 19.2 Contact person for Missing Children Penalty Mail Program. The DOJ contact person for the Missing Children Penalty Mail Program is: Patricia...

28 CFR 19.2 - Contact person for Missing Children Penalty Mail Program.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 28 Judicial Administration 1 2014-07-01 2014-07-01 false Contact person for Missing Children... IN THE LOCATION AND RECOVERY OF MISSING CHILDREN § 19.2 Contact person for Missing Children Penalty Mail Program. The DOJ contact person for the Missing Children Penalty Mail Program is: Patricia...

28 CFR 19.2 - Contact person for Missing Children Penalty Mail Program.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 28 Judicial Administration 1 2011-07-01 2011-07-01 false Contact person for Missing Children... IN THE LOCATION AND RECOVERY OF MISSING CHILDREN § 19.2 Contact person for Missing Children Penalty Mail Program. The DOJ contact person for the Missing Children Penalty Mail Program is: Patricia...

28 CFR 19.2 - Contact person for Missing Children Penalty Mail Program.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 28 Judicial Administration 1 2012-07-01 2012-07-01 false Contact person for Missing Children... IN THE LOCATION AND RECOVERY OF MISSING CHILDREN § 19.2 Contact person for Missing Children Penalty Mail Program. The DOJ contact person for the Missing Children Penalty Mail Program is: Patricia...

40 CFR 98.445 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... Procedures for estimating missing data. A complete record of all measured parameters used in the GHG... following missing data procedures: (a) A quarterly flow rate of CO2 received that is missing must be...

40 CFR 98.126 - Data reporting requirements.

Code of Federal Regulations, 2011 CFR

2011-07-01

... fluorinated GHG emitted from equipment leaks (metric tons). (d) Reporting for missing data. Where missing data have been estimated pursuant to § 98.125, you must report the reason the data were missing, the length of time the data were missing, the method used to estimate the missing data, and the estimates of...

40 CFR 98.145 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... missing data. A complete record of all measured parameters used in the GHG emissions calculations is... in § 98.144 cannot be followed and data is missing, you must use the most appropriate of the missing...

40 CFR 98.245 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... estimating missing data. For missing feedstock flow rates, product flow rates, and carbon contents, use the same procedures as for missing flow rates and carbon contents for fuels as specified in § 98.35. ...

40 CFR 98.385 - Procedures for estimating missing data.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Procedures for estimating missing data... Procedures for estimating missing data. You must follow the procedures for estimating missing data in § 98... estimating missing data for petroleum products in § 98.395 also applies to coal-to-liquid products. ...

40 CFR 98.245 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... estimating missing data. For missing feedstock flow rates, product flow rates, and carbon contents, use the same procedures as for missing flow rates and carbon contents for fuels as specified in § 98.35. ...

The Effect of Missing Data Treatment on Mantel-Haenszel DIF Detection

ERIC Educational Resources Information Center

Emenogu, Barnabas C.; Falenchuk, Olesya; Childs, Ruth A.

2010-01-01

Most implementations of the Mantel-Haenszel differential item functioning procedure delete records with missing responses or replace missing responses with scores of 0. These treatments of missing data make strong assumptions about the causes of the missing data. Such assumptions may be particularly problematic when groups differ in their patterns…

40 CFR 98.245 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... estimating missing data. For missing feedstock flow rates, product flow rates, and carbon contents, use the same procedures as for missing flow rates and carbon contents for fuels as specified in § 98.35. ...

CTEPP STANDARD OPERATING PROCEDURE FOR HANDLING MISSING SAMPLES AND DATA (SOP-2.24)

EPA Science Inventory

This SOP describes the method for handling missing samples or data. Missing samples or data will be identified as soon as possible during field sampling. It provides guidance to collect the missing sample or data and document the reason for the missing sample or data.

Impact of Missing Data on Person-Model Fit and Person Trait Estimation

ERIC Educational Resources Information Center

Zhang, Bo; Walker, Cindy M.

2008-01-01

The purpose of this research was to examine the effects of missing data on person-model fit and person trait estimation in tests with dichotomous items. Under the missing-completely-at-random framework, four missing data treatment techniques were investigated including pairwise deletion, coding missing responses as incorrect, hotdeck imputation,…

40 CFR 98.385 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... Procedures for estimating missing data. You must follow the procedures for estimating missing data in § 98... estimating missing data for petroleum products in § 98.395 also applies to coal-to-liquid products. ...

40 CFR 98.385 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... Procedures for estimating missing data. You must follow the procedures for estimating missing data in § 98... estimating missing data for petroleum products in § 98.395 also applies to coal-to-liquid products. ...

40 CFR 98.385 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... Procedures for estimating missing data. You must follow the procedures for estimating missing data in § 98... estimating missing data for petroleum products in § 98.395 also applies to coal-to-liquid products. ...

40 CFR 98.145 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... missing data. A complete record of all measured parameters used in the GHG emissions calculations is... in § 98.144 cannot be followed and data is missing, you must use the most appropriate of the missing...

40 CFR 98.126 - Data reporting requirements.

Code of Federal Regulations, 2012 CFR

2012-07-01

... fluorinated GHG emitted from equipment leaks (metric tons). (d) Reporting for missing data. Where missing data have been estimated pursuant to § 98.125, you must report the reason the data were missing, the length of time the data were missing, the method used to estimate the missing data, and the estimates of...

40 CFR 98.145 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... missing data. A complete record of all measured parameters used in the GHG emissions calculations is... in § 98.144 cannot be followed and data is missing, you must use the most appropriate of the missing...

40 CFR 98.385 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... Procedures for estimating missing data. You must follow the procedures for estimating missing data in § 98... estimating missing data for petroleum products in § 98.395 also applies to coal-to-liquid products. ...

Planned Missing Data Designs in Educational Psychology Research

ERIC Educational Resources Information Center

Rhemtulla, Mijke; Hancock, Gregory R.

2016-01-01

Although missing data are often viewed as a challenge for applied researchers, in fact missing data can be highly beneficial. Specifically, when the amount of missing data on specific variables is carefully controlled, a balance can be struck between statistical power and research costs. This article presents the issue of planned missing data by…

40 CFR 98.245 - Procedures for estimating missing data.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Procedures for estimating missing data... estimating missing data. For missing feedstock flow rates, product flow rates, and carbon contents, use the same procedures as for missing flow rates and carbon contents for fuels as specified in § 98.35. ...

Statistical analysis and handling of missing data in cluster randomized trials: a systematic review.

PubMed

Fiero, Mallorie H; Huang, Shuang; Oren, Eyal; Bell, Melanie L

2016-02-09

Cluster randomized trials (CRTs) randomize participants in groups, rather than as individuals and are key tools used to assess interventions in health research where treatment contamination is likely or if individual randomization is not feasible. Two potential major pitfalls exist regarding CRTs, namely handling missing data and not accounting for clustering in the primary analysis. The aim of this review was to evaluate approaches for handling missing data and statistical analysis with respect to the primary outcome in CRTs. We systematically searched for CRTs published between August 2013 and July 2014 using PubMed, Web of Science, and PsycINFO. For each trial, two independent reviewers assessed the extent of the missing data and method(s) used for handling missing data in the primary and sensitivity analyses. We evaluated the primary analysis and determined whether it was at the cluster or individual level. Of the 86 included CRTs, 80 (93%) trials reported some missing outcome data. Of those reporting missing data, the median percent of individuals with a missing outcome was 19% (range 0.5 to 90%). The most common way to handle missing data in the primary analysis was complete case analysis (44, 55%), whereas 18 (22%) used mixed models, six (8%) used single imputation, four (5%) used unweighted generalized estimating equations, and two (2%) used multiple imputation. Fourteen (16%) trials reported a sensitivity analysis for missing data, but most assumed the same missing data mechanism as in the primary analysis. Overall, 67 (78%) trials accounted for clustering in the primary analysis. High rates of missing outcome data are present in the majority of CRTs, yet handling missing data in practice remains suboptimal. Researchers and applied statisticians should carry out appropriate missing data methods, which are valid under plausible assumptions in order to increase statistical power in trials and reduce the possibility of bias. Sensitivity analysis should be performed, with weakened assumptions regarding the missing data mechanism to explore the robustness of results reported in the primary analysis.

Purposeful Variable Selection and Stratification to Impute Missing FAST Data in Trauma Research

PubMed Central

Fuchs, Paul A.; del Junco, Deborah J.; Fox, Erin E.; Holcomb, John B.; Rahbar, Mohammad H.; Wade, Charles A.; Alarcon, Louis H.; Brasel, Karen J.; Bulger, Eileen M.; Cohen, Mitchell J.; Myers, John G.; Muskat, Peter; Phelan, Herb A.; Schreiber, Martin A.; Cotton, Bryan A.

2013-01-01

Background The Focused Assessment with Sonography for Trauma (FAST) exam is an important variable in many retrospective trauma studies. The purpose of this study was to devise an imputation method to overcome missing data for the FAST exam. Due to variability in patients’ injuries and trauma care, these data are unlikely to be missing completely at random (MCAR), raising concern for validity when analyses exclude patients with missing values. Methods Imputation was conducted under a less restrictive, more plausible missing at random (MAR) assumption. Patients with missing FAST exams had available data on alternate, clinically relevant elements that were strongly associated with FAST results in complete cases, especially when considered jointly. Subjects with missing data (32.7%) were divided into eight mutually exclusive groups based on selected variables that both described the injury and were associated with missing FAST values. Additional variables were selected within each group to classify missing FAST values as positive or negative, and correct FAST exam classification based on these variables was determined for patients with non-missing FAST values. Results Severe head/neck injury (odds ratio, OR=2.04), severe extremity injury (OR=4.03), severe abdominal injury (OR=1.94), no injury (OR=1.94), other abdominal injury (OR=0.47), other head/neck injury (OR=0.57) and other extremity injury (OR=0.45) groups had significant ORs for missing data; the other group odds ratio was not significant (OR=0.84). All 407 missing FAST values were imputed, with 109 classified as positive. Correct classification of non-missing FAST results using the alternate variables was 87.2%. Conclusions Purposeful imputation for missing FAST exams based on interactions among selected variables assessed by simple stratification may be a useful adjunct to sensitivity analysis in the evaluation of imputation strategies under different missing data mechanisms. This approach has the potential for widespread application in clinical and translational research and validation is warranted. Level of Evidence Level II Prognostic or Epidemiological PMID:23778515

Responsiveness-informed multiple imputation and inverse probability-weighting in cohort studies with missing data that are non-monotone or not missing at random.

PubMed

Doidge, James C

2018-02-01

Population-based cohort studies are invaluable to health research because of the breadth of data collection over time, and the representativeness of their samples. However, they are especially prone to missing data, which can compromise the validity of analyses when data are not missing at random. Having many waves of data collection presents opportunity for participants' responsiveness to be observed over time, which may be informative about missing data mechanisms and thus useful as an auxiliary variable. Modern approaches to handling missing data such as multiple imputation and maximum likelihood can be difficult to implement with the large numbers of auxiliary variables and large amounts of non-monotone missing data that occur in cohort studies. Inverse probability-weighting can be easier to implement but conventional wisdom has stated that it cannot be applied to non-monotone missing data. This paper describes two methods of applying inverse probability-weighting to non-monotone missing data, and explores the potential value of including measures of responsiveness in either inverse probability-weighting or multiple imputation. Simulation studies are used to compare methods and demonstrate that responsiveness in longitudinal studies can be used to mitigate bias induced by missing data, even when data are not missing at random.

Missing persons-missing data: the need to collect antemortem dental records of missing persons.

PubMed

Blau, Soren; Hill, Anthony; Briggs, Christopher A; Cordner, Stephen M

2006-03-01

The subject of missing persons is of great concern to the community with numerous associated emotional, financial, and health costs. This paper examines the forensic medical issues raised by the delayed identification of individuals classified as "missing" and highlights the importance of including dental data in the investigation of missing persons. Focusing on Australia, the current approaches employed in missing persons investigations are outlined. Of particular significance is the fact that each of the eight Australian states and territories has its own Missing Persons Unit that operates within distinct state and territory legislation. Consequently, there is a lack of uniformity within Australia about the legal and procedural framework within which investigations of missing persons are conducted, and the interaction of that framework with coronial law procedures. One of the main investigative problems in missing persons investigations is the lack of forensic medical, particularly, odontological input. Forensic odontology has been employed in numerous cases in Australia where identity is unknown or uncertain because of remains being skeletonized, incinerated, or partly burnt. The routine employment of the forensic odontologist to assist in missing person inquiries, has however, been ignored. The failure to routinely employ forensic odontology in missing persons inquiries has resulted in numerous delays in identification. Three Australian cases are presented where the investigation of individuals whose identity was uncertain or unknown was prolonged due to the failure to utilize the appropriate (and available) dental resources. In light of the outcomes of these cases, we suggest that a national missing persons dental records database be established for future missing persons investigations. Such a database could be easily managed between a coronial system and a forensic medical institute. In Australia, a national missing persons dental records database could be incorporated into the National Coroners Information System (NCIS) managed, on behalf of Australia's Coroners, by the Victorian Institute of Forensic Medicine. The existence of the NCIS would ensure operational collaboration in the implementation of the system and cost savings to Australian policing agencies involved in missing person inquiries. The implementation of such a database would facilitate timely and efficient reconciliation of clinical and postmortem dental records and have subsequent social and financial benefits.

Potentially Missed Diagnosis of Ischemic Stroke in the Emergency Department in the Greater Cincinnati/Northern Kentucky Stroke Study.

PubMed

Madsen, Tracy E; Khoury, Jane; Cadena, Rhonda; Adeoye, Opeolu; Alwell, Kathleen A; Moomaw, Charles J; McDonough, Erin; Flaherty, Matthew L; Ferioli, Simona; Woo, Daniel; Khatri, Pooja; Broderick, Joseph P; Kissela, Brett M; Kleindorfer, Dawn

2016-10-01

Missed diagnoses of acute ischemic stroke (AIS) in the ED may result in lost opportunities to treat AIS. Our objectives were to describe the rate and clinical characteristics of missed AIS in the ED, to determine clinical predictors of missed AIS, and to report tissue plasminogen (tPA) eligibility among those with missed strokes. Among a population of 1.3 million in a five-county region of southwest Ohio and northern Kentucky, cases of AIS that presented to 16 EDs during 2010 were identified using ICD-9 codes followed by physician verification of cases. Missed ED diagnoses were physician-verified strokes that did not receive a diagnosis indicative of stroke in the ED. Bivariate analyses were used to compare clinical characteristics between patients with and without an ED diagnosis of AIS. Logistic regression was used to evaluate predictors of missed AIS diagnoses. Alternative diagnoses given to those with missed AIS were codified. Eligibility for tPA was reported between those with and without a missed stroke diagnosis. Of 2,027 AIS cases, 14.0% (n = 283) were missed in the ED. Race, sex, and stroke subtypes were similar between those with missed AIS diagnoses and those identified in the ED. Hospital length of stay was longer in those with a missed diagnosis (5 days vs. 3 days, p < 0.0001). Younger age (adjusted odds ratio [aOR] = 0.94, 95% confidence interval [CI] = 0.89 to 0.98) and decreased level of consciousness (LOC) (aOR = 3.58, 95% CI = 2.63 to 4.87) were associated with higher odds of missed AIS. Altered mental status was the most common diagnosis among those with missed AIS. Only 1.1% of those with a missed stroke diagnosis were eligible for tPA. In a large population-based sample of AIS cases, one in seven cases were not diagnosed as AIS in the ED, but the impact on acute treatment rates is likely small. Missed diagnosis was more common among those with decreased LOC, suggesting the need for improved diagnostic approaches in these patients. © 2016 by the Society for Academic Emergency Medicine.

Results of Database Studies in Spine Surgery Can Be Influenced by Missing Data.

PubMed

Basques, Bryce A; McLynn, Ryan P; Fice, Michael P; Samuel, Andre M; Lukasiewicz, Adam M; Bohl, Daniel D; Ahn, Junyoung; Singh, Kern; Grauer, Jonathan N

2017-12-01

National databases are increasingly being used for research in spine surgery; however, one limitation of such databases that has received sparse mention is the frequency of missing data. Studies using these databases often do not emphasize the percentage of missing data for each variable used and do not specify how patients with missing data are incorporated into analyses. This study uses the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database to examine whether different treatments of missing data can influence the results of spine studies. (1) What is the frequency of missing data fields for demographics, medical comorbidities, preoperative laboratory values, operating room times, and length of stay recorded in ACS-NSQIP? (2) Using three common approaches to handling missing data, how frequently do those approaches agree in terms of finding particular variables to be associated with adverse events? (3) Do different approaches to handling missing data influence the outcomes and effect sizes of an analysis testing for an association with these variables with occurrence of adverse events? Patients who underwent spine surgery between 2005 and 2013 were identified from the ACS-NSQIP database. A total of 88,471 patients undergoing spine surgery were identified. The most common procedures were anterior cervical discectomy and fusion, lumbar decompression, and lumbar fusion. Demographics, comorbidities, and perioperative laboratory values were tabulated for each patient, and the percent of missing data was noted for each variable. These variables were tested for an association with "any adverse event" using three separate multivariate regressions that used the most common treatments for missing data. In the first regression, patients with any missing data were excluded. In the second regression, missing data were treated as a negative or "reference" value; for continuous variables, the mean of each variable's reference range was computed and imputed. In the third regression, any variables with > 10% rate of missing data were removed from the regression; among variables with ≤ 10% missing data, individual cases with missing values were excluded. The results of these regressions were compared to determine how the different treatments of missing data could affect the results of spine studies using the ACS-NSQIP database. Of the 88,471 patients, as many as 4441 (5%) had missing elements among demographic data, 69,184 (72%) among comorbidities, 70,892 (80%) among preoperative laboratory values, and 56,551 (64%) among operating room times. Considering the three different treatments of missing data, we found different risk factors for adverse events. Of 44 risk factors found to be associated with adverse events in any analysis, only 15 (34%) of these risk factors were common among the three regressions. The second treatment of missing data (assuming "normal" value) found the most risk factors (40) to be associated with any adverse event, whereas the first treatment (deleting patients with missing data) found the fewest associations at 20. Among the risk factors associated with any adverse event, the 10 with the greatest effect size (odds ratio) by each regression were ranked. Of the 15 variables in the top 10 for any regression, six of these were common among all three lists. Differing treatments of missing data can influence the results of spine studies using the ACS-NSQIP. The current study highlights the importance of considering how such missing data are handled. Until there are better guidelines on the best approaches to handle missing data, investigators should report how missing data were handled to increase the quality and transparency of orthopaedic database research. Readers of large database studies should note whether handling of missing data was addressed and consider potential bias with high rates or unspecified or weak methods for handling missing data.

Using Monte Carlo Simulations to Determine Power and Sample Size for Planned Missing Designs

ERIC Educational Resources Information Center

Schoemann, Alexander M.; Miller, Patrick; Pornprasertmanit, Sunthud; Wu, Wei

2014-01-01

Planned missing data designs allow researchers to increase the amount and quality of data collected in a single study. Unfortunately, the effect of planned missing data designs on power is not straightforward. Under certain conditions using a planned missing design will increase power, whereas in other situations using a planned missing design…

The Impact of the Nursing Practice Environment on Missed Nursing Care.

PubMed

Hessels, Amanda J; Flynn, Linda; Cimiotti, Jeannie P; Cadmus, Edna; Gershon, Robyn R M

2015-12-01

Missed nursing care is an emerging problem negatively impacting patient outcomes. There are gaps in our knowledge of factors associated with missed nursing care. The aim of this study was to determine the relationship between the nursing practice environment and missed nursing care in acute care hospitals. This is a secondary analysis of cross sectional data from a survey of over 7.000 nurses from 70 hospitals on workplace and process of care. Ordinary least squares and multiple regression models were constructed to examine the relationship between the nursing practice environment and missed nursing care while controlling for characteristics of nurses and hospitals. Nurses missed delivering a significant amount of necessary patient care (10-27%). Inadequate staffing and inadequate resources were the practice environment factors most strongly associated with missed nursing care events. This multi-site study examined the risk and risk factors associated with missed nursing care. Improvements targeting modifiable risk factors may reduce the risk of missed nursing care.

Use of an Aerodynamic Turn to Maximize the Orbit Inclination Change for the Space Shuttle Orbiter.

DTIC Science & Technology

1979-12-01

0 9 3 p s B A N K A, . 01 . 2 0 d e g ALT MiS -3.57 -0.21 -22.91 m 15. VEL T .009 .005 .00 k s Ai .15 .17 .22 deg ALT ISS -5.66 -12.66 -26.04...ALT MISS 32 7 29. 1 22.5 km 0 VEL MISS -.01. 16 -.018 ,S 0. 0. 0. ALT mISS 31.9 9m 50 VEL MISS -.010 - .016 -. 018 "ps .03 .04 .0- eg ANGLE ALT MISS...31.4 9.1 2_.9 km OF 10 VEL MISS -. 0101 kps Ao .06 .07 .09 dec AL MISS 31.6 27.1 19.5 15 ° VEL MISS -. 010 -. 015 -. 017 kps ,\\i .08 .11 .13 deg ALT

Missing value imputation: with application to handwriting data

NASA Astrophysics Data System (ADS)

Xu, Zhen; Srihari, Sargur N.

2015-01-01

Missing values make pattern analysis difficult, particularly with limited available data. In longitudinal research, missing values accumulate, thereby aggravating the problem. Here we consider how to deal with temporal data with missing values in handwriting analysis. In the task of studying development of individuality of handwriting, we encountered the fact that feature values are missing for several individuals at several time instances. Six algorithms, i.e., random imputation, mean imputation, most likely independent value imputation, and three methods based on Bayesian network (static Bayesian network, parameter EM, and structural EM), are compared with children's handwriting data. We evaluate the accuracy and robustness of the algorithms under different ratios of missing data and missing values, and useful conclusions are given. Specifically, static Bayesian network is used for our data which contain around 5% missing data to provide adequate accuracy and low computational cost.

Identifying patterns of item missing survey data using latent groups: an observational study.

PubMed

Barnett, Adrian G; McElwee, Paul; Nathan, Andrea; Burton, Nicola W; Turrell, Gavin

2017-10-30

To examine whether respondents to a survey of health and physical activity and potential determinants could be grouped according to the questions they missed, known as 'item missing'. Observational study of longitudinal data. Residents of Brisbane, Australia. 6901 people aged 40-65 years in 2007. We used a latent class model with a mixture of multinomial distributions and chose the number of classes using the Bayesian information criterion. We used logistic regression to examine if participants' characteristics were associated with their modal latent class. We used logistic regression to examine whether the amount of item missing in a survey predicted wave missing in the following survey. Four per cent of participants missed almost one-fifth of the questions, and this group missed more questions in the middle of the survey. Eighty-three per cent of participants completed almost every question, but had a relatively high missing probability for a question on sleep time, a question which had an inconsistent presentation compared with the rest of the survey. Participants who completed almost every question were generally younger and more educated. Participants who completed more questions were less likely to miss the next longitudinal wave. Examining patterns in item missing data has improved our understanding of how missing data were generated and has informed future survey design to help reduce missing data. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Examining solutions to missing data in longitudinal nursing research.

PubMed

Roberts, Mary B; Sullivan, Mary C; Winchester, Suzy B

2017-04-01

Longitudinal studies are highly valuable in pediatrics because they provide useful data about developmental patterns of child health and behavior over time. When data are missing, the value of the research is impacted. The study's purpose was to (1) introduce a three-step approach to assess and address missing data and (2) illustrate this approach using categorical and continuous-level variables from a longitudinal study of premature infants. A three-step approach with simulations was followed to assess the amount and pattern of missing data and to determine the most appropriate imputation method for the missing data. Patterns of missingness were Missing Completely at Random, Missing at Random, and Not Missing at Random. Missing continuous-level data were imputed using mean replacement, stochastic regression, multiple imputation, and fully conditional specification (FCS). Missing categorical-level data were imputed using last value carried forward, hot-decking, stochastic regression, and FCS. Simulations were used to evaluate these imputation methods under different patterns of missingness at different levels of missing data. The rate of missingness was 16-23% for continuous variables and 1-28% for categorical variables. FCS imputation provided the least difference in mean and standard deviation estimates for continuous measures. FCS imputation was acceptable for categorical measures. Results obtained through simulation reinforced and confirmed these findings. Significant investments are made in the collection of longitudinal data. The prudent handling of missing data can protect these investments and potentially improve the scientific information contained in pediatric longitudinal studies. © 2017 Wiley Periodicals, Inc.

Teaching Missing Data Methodology to Undergraduates Using a Group-Based Project within a Six-Week Summer Program

ERIC Educational Resources Information Center

Marron, Megan M.; Wahed, Abdus S.

2016-01-01

Missing data mechanisms, methods of handling missing data, and the potential impact of missing data on study results are usually not taught until graduate school. However, the appropriate handling of missing data is fundamental to biomedical research and should be introduced earlier on in a student's education. The Summer Institute for Training in…

Statistical inference for Hardy-Weinberg proportions in the presence of missing genotype information.

PubMed

Graffelman, Jan; Sánchez, Milagros; Cook, Samantha; Moreno, Victor

2013-01-01

In genetic association studies, tests for Hardy-Weinberg proportions are often employed as a quality control checking procedure. Missing genotypes are typically discarded prior to testing. In this paper we show that inference for Hardy-Weinberg proportions can be biased when missing values are discarded. We propose to use multiple imputation of missing values in order to improve inference for Hardy-Weinberg proportions. For imputation we employ a multinomial logit model that uses information from allele intensities and/or neighbouring markers. Analysis of an empirical data set of single nucleotide polymorphisms possibly related to colon cancer reveals that missing genotypes are not missing completely at random. Deviation from Hardy-Weinberg proportions is mostly due to a lack of heterozygotes. Inbreeding coefficients estimated by multiple imputation of the missings are typically lowered with respect to inbreeding coefficients estimated by discarding the missings. Accounting for missings by multiple imputation qualitatively changed the results of 10 to 17% of the statistical tests performed. Estimates of inbreeding coefficients obtained by multiple imputation showed high correlation with estimates obtained by single imputation using an external reference panel. Our conclusion is that imputation of missing data leads to improved statistical inference for Hardy-Weinberg proportions.

Missing value imputation strategies for metabolomics data.

PubMed

Armitage, Emily Grace; Godzien, Joanna; Alonso-Herranz, Vanesa; López-Gonzálvez, Ángeles; Barbas, Coral

2015-12-01

The origin of missing values can be caused by different reasons and depending on these origins missing values should be considered differently and dealt with in different ways. In this research, four methods of imputation have been compared with respect to revealing their effects on the normality and variance of data, on statistical significance and on the approximation of a suitable threshold to accept missing data as truly missing. Additionally, the effects of different strategies for controlling familywise error rate or false discovery and how they work with the different strategies for missing value imputation have been evaluated. Missing values were found to affect normality and variance of data and k-means nearest neighbour imputation was the best method tested for restoring this. Bonferroni correction was the best method for maximizing true positives and minimizing false positives and it was observed that as low as 40% missing data could be truly missing. The range between 40 and 70% missing values was defined as a "gray area" and therefore a strategy has been proposed that provides a balance between the optimal imputation strategy that was k-means nearest neighbor and the best approximation of positioning real zeros. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Missing data within a quantitative research study: How to assess it, treat it, and why you should care.

PubMed

Bannon, William

2015-04-01

Missing data typically refer to the absence of one or more values within a study variable(s) contained in a dataset. The development is often the result of a study participant choosing not to provide a response to a survey item. In general, a greater number of missing values within a dataset reflects a greater challenge to the data analyst. However, if researchers are armed with just a few basic tools, they can quite effectively diagnose how serious the issue of missing data is within a dataset, as well as prescribe the most appropriate solution. Specifically, the keys to effectively assessing and treating missing data values within a dataset involve specifying how missing data will be defined in a study, assessing the amount of missing data, identifying the pattern of the missing data, and selecting the best way to treat the missing data values. I will touch on each of these processes and provide a brief illustration of how the validity of study findings are at great risk if missing data values are not treated effectively. ©2015 American Association of Nurse Practitioners.

Impact of teamwork on missed care in four Australian hospitals.

PubMed

Chapman, Rose; Rahman, Asheq; Courtney, Mary; Chalmers, Cheyne

2017-01-01

Investigate effects of teamwork on missed nursing care across a healthcare network in Australia. Missed care is universally used as an indicator of quality nursing care, however, little is known about mitigating effects of teamwork on these events. A descriptive exploratory study. Missed Care and Team Work surveys were completed by 334 nurses. Using Stata software, nursing staff demographic information and components of missed care and teamwork were compared across the healthcare network. Statistical tests were performed to identify predicting factors for missed care. The most commonly reported components of missed care were as follows: ambulation three times per day (43·3%), turning patient every two hours (29%) and mouth care (27·7%). The commonest reasons mentioned for missed care were as follows: inadequate labour resources (range 69·8-52·7%), followed by material resources (range 59·3-33·3%) and communication (range 39·3-27·2%). There were significant differences in missed care scores across units. Using the mean scores in regression correlation matrix, the negative relationship of missed care and teamwork was supported (r = -0·34, p < 0·001). Controlling for occupation of the staff member and staff characteristics in multiple regression models, teamwork alone accounted for about 9% of missed nursing care. Similar to previous international research findings, our results showed nursing teamwork significantly impacted on missed nursing care. Teamwork may be a mitigating factor to address missed care and future research is needed. These results may provide administrators, educators and clinicians with information to develop practices and policies to improve patient care internationally. © 2016 John Wiley & Sons Ltd.

Why are they missing? : Bioinformatics characterization of missing human proteins.

PubMed

Elguoshy, Amr; Magdeldin, Sameh; Xu, Bo; Hirao, Yoshitoshi; Zhang, Ying; Kinoshita, Naohiko; Takisawa, Yusuke; Nameta, Masaaki; Yamamoto, Keiko; El-Refy, Ali; El-Fiky, Fawzy; Yamamoto, Tadashi

2016-10-21

NeXtProt is a web-based protein knowledge platform that supports research on human proteins. NeXtProt (release 2015-04-28) lists 20,060 proteins, among them, 3373 canonical proteins (16.8%) lack credible experimental evidence at protein level (PE2:PE5). Therefore, they are considered as "missing proteins". A comprehensive bioinformatic workflow has been proposed to analyze these "missing" proteins. The aims of current study were to analyze physicochemical properties, existence and distribution of the tryptic cleavage sites, and to pinpoint the signature peptides of the missing proteins. Our findings showed that 23.7% of missing proteins were hydrophobic proteins possessing transmembrane domains (TMD). Also, forty missing entries generate tryptic peptides were either out of mass detection range (>30aa) or mapped to different proteins (<9aa). Additionally, 21% of missing entries didn't generate any unique tryptic peptides. In silico endopeptidase combination strategy increased the possibility of missing proteins identification. Coherently, using both mature protein database and signal peptidome database could be a promising option to identify some missing proteins by targeting their unique N-terminal tryptic peptide from mature protein database and or C-terminus tryptic peptide from signal peptidome database. In conclusion, Identification of missing protein requires additional consideration during sample preparation, extraction, digestion and data analysis to increase its incidence of identification. Copyright © 2016. Published by Elsevier B.V.

Identifying patterns of item missing survey data using latent groups: an observational study

PubMed Central

McElwee, Paul; Nathan, Andrea; Burton, Nicola W; Turrell, Gavin

2017-01-01

Objectives To examine whether respondents to a survey of health and physical activity and potential determinants could be grouped according to the questions they missed, known as ‘item missing’. Design Observational study of longitudinal data. Setting Residents of Brisbane, Australia. Participants 6901 people aged 40–65 years in 2007. Materials and methods We used a latent class model with a mixture of multinomial distributions and chose the number of classes using the Bayesian information criterion. We used logistic regression to examine if participants’ characteristics were associated with their modal latent class. We used logistic regression to examine whether the amount of item missing in a survey predicted wave missing in the following survey. Results Four per cent of participants missed almost one-fifth of the questions, and this group missed more questions in the middle of the survey. Eighty-three per cent of participants completed almost every question, but had a relatively high missing probability for a question on sleep time, a question which had an inconsistent presentation compared with the rest of the survey. Participants who completed almost every question were generally younger and more educated. Participants who completed more questions were less likely to miss the next longitudinal wave. Conclusions Examining patterns in item missing data has improved our understanding of how missing data were generated and has informed future survey design to help reduce missing data. PMID:29084795

Association of the Nurse Work Environment, Collective Efficacy, and Missed Care.

PubMed

Smith, Jessica G; Morin, Karen H; Wallace, Leigh E; Lake, Eileen T

2018-06-01

Missed nursing care is a significant threat to quality patient care. Promoting collective efficacy within nurse work environments could decrease missed care. The purpose was to understand how missed care is associated with nurse work environments and collective efficacy of hospital staff nurses. A cross-sectional, convenience sample was obtained through online surveys from registered nurses working at five southwestern U.S. hospitals. Descriptive, correlational, regression, and path analyses were conducted ( N = 233). The percentage of nurses who reported that at least one care activity was missed frequently or always was 94%. Mouth care (36.0% of nurses) and ambulation (35.3%) were missed frequently or always. Nurse work environments and collective efficacy were moderately, positively correlated. Nurse work environments and collective efficacy were associated with less missed care (χ 2 = 10.714, p = .0054). Fostering collective efficacy in the nurse work environment could reduce missed care and improve patient outcomes.

Considerations of multiple imputation approaches for handling missing data in clinical trials.

PubMed

Quan, Hui; Qi, Li; Luo, Xiaodong; Darchy, Loic

2018-07-01

Missing data exist in all clinical trials and missing data issue is a very serious issue in terms of the interpretability of the trial results. There is no universally applicable solution for all missing data problems. Methods used for handling missing data issue depend on the circumstances particularly the assumptions on missing data mechanisms. In recent years, if the missing at random mechanism cannot be assumed, conservative approaches such as the control-based and returning to baseline multiple imputation approaches are applied for dealing with the missing data issues. In this paper, we focus on the variability in data analysis of these approaches. As demonstrated by examples, the choice of the variability can impact the conclusion of the analysis. Besides the methods for continuous endpoints, we also discuss methods for binary and time to event endpoints as well as consideration for non-inferiority assessment. Copyright © 2018. Published by Elsevier Inc.

A review of the handling of missing longitudinal outcome data in clinical trials

PubMed Central

2014-01-01

The aim of this review was to establish the frequency with which trials take into account missingness, and to discover what methods trialists use for adjustment in randomised controlled trials with longitudinal measurements. Failing to address the problems that can arise from missing outcome data can result in misleading conclusions. Missing data should be addressed as a means of a sensitivity analysis of the complete case analysis results. One hundred publications of randomised controlled trials with longitudinal measurements were selected randomly from trial publications from the years 2005 to 2012. Information was extracted from these trials, including whether reasons for dropout were reported, what methods were used for handing the missing data, whether there was any explanation of the methods for missing data handling, and whether a statistician was involved in the analysis. The main focus of the review was on missing data post dropout rather than missing interim data. Of all the papers in the study, 9 (9%) had no missing data. More than half of the papers included in the study failed to make any attempt to explain the reasons for their choice of missing data handling method. Of the papers with clear missing data handling methods, 44 papers (50%) used adequate methods of missing data handling, whereas 30 (34%) of the papers used missing data methods which may not have been appropriate. In the remaining 17 papers (19%), it was difficult to assess the validity of the methods used. An imputation method was used in 18 papers (20%). Multiple imputation methods were introduced in 1987 and are an efficient way of accounting for missing data in general, and yet only 4 papers used these methods. Out of the 18 papers which used imputation, only 7 displayed the results as a sensitivity analysis of the complete case analysis results. 61% of the papers that used an imputation explained the reasons for their chosen method. Just under a third of the papers made no reference to reasons for missing outcome data. There was little consistency in reporting of missing data within longitudinal trials. PMID:24947664

Comparison of minimally invasive spine surgery using intraoperative computed tomography integrated navigation, fluoroscopy, and conventional open surgery for lumbar spondylolisthesis: a prospective registry-based cohort study.

PubMed

Wu, Meng-Huang; Dubey, Navneet Kumar; Li, Yen-Yao; Lee, Ching-Yu; Cheng, Chin-Chang; Shi, Chung-Sheng; Huang, Tsung-Jen

2017-08-01

To date, the surgical approaches for the treatment of lumbar spondylolisthesis by transforaminal lumbar interbody fusion (TLIF) using minimally invasive spine surgery assisted with intraoperative computed tomography image-integrated navigation (MISS-iCT), fluoroscopy (MISS-FS), and conventional open surgery (OS) are debatable. This study compared TLIF using MISS-iCT, MISS-FS, and OS for treatment of one-level lumbar spondylolisthesis. This is a prospective, registry-based cohort study that compared surgical approaches for patients who underwent surgical treatment for one-level lumbar spondylolisthesis. One hundred twenty-four patients from January 2010 to March 2012 in a medical center were recruited. The outcome measures were clinical assessments, including Short-Form 12, visual analog scale (VAS), Oswestry Disability Index, Core Outcome Measurement Index, and patient satisfaction, and blood loss, hospital stay, operation time, postoperative pedicle screw accuracy, and superior-level facet violation. All surgeries were performed by two senior surgeons together. Ninety-nine patients (40M, 59F) who had at least 2 years' follow-up were divided into three groups according to the operation methods: MISS-iCT (N=24), MISS-FS (N=23), and OS (N=52) groups. Charts and surgical records along with postoperative CT images were assessed. MISS-iCT and MISS-FS demonstrated a significantly lowered blood loss and hospital stay compared with OS group (p<.01). Operation time was significantly lower in the MISS-iCT and OS groups compared with the MISS-FS group (p=.002). Postoperatively, VAS scores at 1 year and 2 years were significantly improved in the MISS-iCT and MISS-FS groups compared with the OS groups. No significant difference in the number of pedicle screw breach (>2 mm) was found. However, a lower superior-level facet violation rate was observed in the MISS-iCT and OS groups (p=.049). MISS-iCT TLIF demonstrated reduced operation time, blood loss, superior-level facet violation, hospital stay, and improved functional outcomes compared with the MISS-FS and OS approaches. Copyright © 2017 Elsevier Inc. All rights reserved.

Examining Solutions to Missing Data in Longitudinal Nursing Research

PubMed Central

Roberts, Mary B.; Sullivan, Mary C.; Winchester, Suzy B.

2017-01-01

Purpose Longitudinal studies are highly valuable in pediatrics because they provide useful data about developmental patterns of child health and behavior over time. When data are missing, the value of the research is impacted. The study’s purpose was to: (1) introduce a 3-step approach to assess and address missing data; (2) illustrate this approach using categorical and continuous level variables from a longitudinal study of premature infants. Methods A three-step approach with simulations was followed to assess the amount and pattern of missing data and to determine the most appropriate imputation method for the missing data. Patterns of missingness were Missing Completely at Random, Missing at Random, and Not Missing at Random. Missing continuous-level data were imputed using mean replacement, stochastic regression, multiple imputation, and fully conditional specification. Missing categorical-level data were imputed using last value carried forward, hot-decking, stochastic regression, and fully conditional specification. Simulations were used to evaluate these imputation methods under different patterns of missingness at different levels of missing data. Results The rate of missingness was 16–23% for continuous variables and 1–28% for categorical variables. Fully conditional specification imputation provided the least difference in mean and standard deviation estimates for continuous measures. Fully conditional specification imputation was acceptable for categorical measures. Results obtained through simulation reinforced and confirmed these findings. Practice Implications Significant investments are made in the collection of longitudinal data. The prudent handling of missing data can protect these investments and potentially improve the scientific information contained in pediatric longitudinal studies. PMID:28425202

Missed injuries during the initial assessment in a cohort of 1124 level-1 trauma patients.

PubMed

Giannakopoulos, G F; Saltzherr, T P; Beenen, L F M; Reitsma, J B; Bloemers, F W; Goslings, J C; Bakker, F C

2012-09-01

Despite the presence of diagnostic guidelines for the initial evaluation in trauma, the reported incidence of missed injuries is considerable. The aim of this study was to assess the missed injuries in a large cohort of trauma patients originating from two European Level-1 trauma centres. We analysed the 1124 patients included in the randomised REACT trial. Missed injuries were defined as injuries not diagnosed or suspected during initial clinical and radiological evaluation in the trauma room. We assessed the frequency, type, consequences and the phase in which the missed injuries were diagnosed and used univariate analysis to identify potential contributing factors. Eight hundred and three patients were male, median age was 38 years and 1079 patients sustained blunt trauma. Overall, 122 injuries were missed in 92 patients (8.2%). Most injuries concerned the extremities. Sixteen injuries had an AIS grade of ≥ 3. Patients with missed injuries had significantly higher injury severity scores (ISSs) (median of 15 versus 5, p<0.001). Factors associated with missed injuries were severe traumatic brain injury (GCS ≤ 8) and multitrauma (ISS ≥ 16). Seventy-two missed injuries remained undetected during tertiary survey (59%). In total, 31 operations were required for 26 initially missed injuries. Despite guidelines to avoid missed injuries, this problem is hard to prevent, especially in the severely injured. The present study showed that the rate of missed injuries was comparable with the literature and their consequences not severe. A high index of suspicion remains warranted, especially in multitrauma patients. Copyright © 2011 Elsevier Ltd. All rights reserved.

Sensitivity Analysis of Multiple Informant Models When Data are Not Missing at Random

PubMed Central

Blozis, Shelley A.; Ge, Xiaojia; Xu, Shu; Natsuaki, Misaki N.; Shaw, Daniel S.; Neiderhiser, Jenae; Scaramella, Laura; Leve, Leslie; Reiss, David

2014-01-01

Missing data are common in studies that rely on multiple informant data to evaluate relationships among variables for distinguishable individuals clustered within groups. Estimation of structural equation models using raw data allows for incomplete data, and so all groups may be retained even if only one member of a group contributes data. Statistical inference is based on the assumption that data are missing completely at random or missing at random. Importantly, whether or not data are missing is assumed to be independent of the missing data. A saturated correlates model that incorporates correlates of the missingness or the missing data into an analysis and multiple imputation that may also use such correlates offer advantages over the standard implementation of SEM when data are not missing at random because these approaches may result in a data analysis problem for which the missingness is ignorable. This paper considers these approaches in an analysis of family data to assess the sensitivity of parameter estimates to assumptions about missing data, a strategy that may be easily implemented using SEM software. PMID:25221420

Near-misses are an opportunity to improve patient safety: adapting strategies of high reliability organizations to healthcare.

PubMed

Van Spall, Harriette; Kassam, Alisha; Tollefson, Travis T

2015-08-01

Near-miss investigations in high reliability organizations (HROs) aim to mitigate risk and improve system safety. Healthcare settings have a higher rate of near-misses and subsequent adverse events than most high-risk industries, but near-misses are not systematically reported or analyzed. In this review, we will describe the strategies for near-miss analysis that have facilitated a culture of safety and continuous quality improvement in HROs. Near-miss analysis is routine and systematic in HROs such as aviation. Strategies implemented in aviation include the Commercial Aviation Safety Team, which undertakes systematic analyses of near-misses, so that findings can be incorporated into Standard Operating Procedures (SOPs). Other strategies resulting from incident analyses include Crew Resource Management (CRM) for enhanced communication, situational awareness training, adoption of checklists during operations, and built-in redundancy within systems. Health care organizations should consider near-misses as opportunities for quality improvement. The systematic reporting and analysis of near-misses, commonplace in HROs, can be adapted to health care settings to prevent adverse events and improve clinical outcomes.

Performance of the CMS missing transverse momentum reconstruction in pp data at $$\\sqrt{s}$$ = 8 TeV

DOE PAGES

Khachatryan, Vardan

2015-02-12

The performance of missing transverse energy reconstruction algorithms is presented by our team using√s=8 TeV proton-proton (pp) data collected with the CMS detector. Events with anomalous missing transverse energy are studied, and the performance of algorithms used to identify and remove these events is presented. The scale and resolution for missing transverse energy, including the effects of multiple pp interactions (pileup), are measured using events with an identified Z boson or isolated photon, and are found to be well described by the simulation. Novel missing transverse energy reconstruction algorithms developed specifically to mitigate the effects of large numbers of pileupmore » interactions on the missing transverse energy resolution are presented. These algorithms significantly reduce the dependence of the missing transverse energy resolution on pileup interactions. Furthermore, an algorithm that provides an estimate of the significance of the missing transverse energy is presented, which is used to estimate the compatibility of the reconstructed missing transverse energy with a zero nominal value.« less

List based prefetch

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boyle, Peter; Christ, Norman; Gara, Alan

A list prefetch engine improves a performance of a parallel computing system. The list prefetch engine receives a current cache miss address. The list prefetch engine evaluates whether the current cache miss address is valid. If the current cache miss address is valid, the list prefetch engine compares the current cache miss address and a list address. A list address represents an address in a list. A list describes an arbitrary sequence of prior cache miss addresses. The prefetch engine prefetches data according to the list, if there is a match between the current cache miss address and the listmore » address.« less

List based prefetch

DOEpatents

Boyle, Peter [Edinburgh, GB; Christ, Norman [Irvington, NY; Gara, Alan [Yorktown Heights, NY; Kim,; Changhoan, [San Jose, CA; Mawhinney, Robert [New York, NY; Ohmacht, Martin [Yorktown Heights, NY; Sugavanam, Krishnan [Yorktown Heights, NY

2012-08-28

A list prefetch engine improves a performance of a parallel computing system. The list prefetch engine receives a current cache miss address. The list prefetch engine evaluates whether the current cache miss address is valid. If the current cache miss address is valid, the list prefetch engine compares the current cache miss address and a list address. A list address represents an address in a list. A list describes an arbitrary sequence of prior cache miss addresses. The prefetch engine prefetches data according to the list, if there is a match between the current cache miss address and the list address.

Longitudinal data analysis with non-ignorable missing data.

PubMed

Tseng, Chi-hong; Elashoff, Robert; Li, Ning; Li, Gang

2016-02-01

A common problem in the longitudinal data analysis is the missing data problem. Two types of missing patterns are generally considered in statistical literature: monotone and non-monotone missing data. Nonmonotone missing data occur when study participants intermittently miss scheduled visits, while monotone missing data can be from discontinued participation, loss to follow-up, and mortality. Although many novel statistical approaches have been developed to handle missing data in recent years, few methods are available to provide inferences to handle both types of missing data simultaneously. In this article, a latent random effects model is proposed to analyze longitudinal outcomes with both monotone and non-monotone missingness in the context of missing not at random. Another significant contribution of this article is to propose a new computational algorithm for latent random effects models. To reduce the computational burden of high-dimensional integration problem in latent random effects models, we develop a new computational algorithm that uses a new adaptive quadrature approach in conjunction with the Taylor series approximation for the likelihood function to simplify the E-step computation in the expectation-maximization algorithm. Simulation study is performed and the data from the scleroderma lung study are used to demonstrate the effectiveness of this method. © The Author(s) 2012.

On analyzing ordinal data when responses and covariates are both missing at random.

PubMed

Rana, Subrata; Roy, Surupa; Das, Kalyan

2016-08-01

In many occasions, particularly in biomedical studies, data are unavailable for some responses and covariates. This leads to biased inference in the analysis when a substantial proportion of responses or a covariate or both are missing. Except a few situations, methods for missing data have earlier been considered either for missing response or for missing covariates, but comparatively little attention has been directed to account for both missing responses and missing covariates, which is partly attributable to complexity in modeling and computation. This seems to be important as the precise impact of substantial missing data depends on the association between two missing data processes as well. The real difficulty arises when the responses are ordinal by nature. We develop a joint model to take into account simultaneously the association between the ordinal response variable and covariates and also that between the missing data indicators. Such a complex model has been analyzed here by using the Markov chain Monte Carlo approach and also by the Monte Carlo relative likelihood approach. Their performance on estimating the model parameters in finite samples have been looked into. We illustrate the application of these two methods using data from an orthodontic study. Analysis of such data provides some interesting information on human habit. © The Author(s) 2013.

Establishing a threshold for the number of missing days using 7 d pedometer data.

PubMed

Kang, Minsoo; Hart, Peter D; Kim, Youngdeok

2012-11-01

The purpose of this study was to examine the threshold of the number of missing days of recovery using the individual information (II)-centered approach. Data for this study came from 86 participants, aged from 17 to 79 years old, who had 7 consecutive days of complete pedometer (Yamax SW 200) wear. Missing datasets (1 d through 5 d missing) were created by a SAS random process 10,000 times each. All missing values were replaced using the II-centered approach. A 7 d average was calculated for each dataset, including the complete dataset. Repeated measure ANOVA was used to determine the differences between 1 d through 5 d missing datasets and the complete dataset. Mean absolute percentage error (MAPE) was also computed. Mean (SD) daily step count for the complete 7 d dataset was 7979 (3084). Mean (SD) values for the 1 d through 5 d missing datasets were 8072 (3218), 8066 (3109), 7968 (3273), 7741 (3050) and 8314 (3529), respectively (p > 0.05). The lower MAPEs were estimated for 1 d missing (5.2%, 95% confidence interval (CI) 4.4-6.0) and 2 d missing (8.4%, 95% CI 7.0-9.8), while all others were greater than 10%. The results of this study show that the 1 d through 5 d missing datasets, with replaced values, were not significantly different from the complete dataset. Based on the MAPE results, it is not recommended to replace more than two days of missing step counts.

Can statistical linkage of missing variables reduce bias in treatment effect estimates in comparative effectiveness research studies?

PubMed

Crown, William; Chang, Jessica; Olson, Melvin; Kahler, Kristijan; Swindle, Jason; Buzinec, Paul; Shah, Nilay; Borah, Bijan

2015-09-01

Missing data, particularly missing variables, can create serious analytic challenges in observational comparative effectiveness research studies. Statistical linkage of datasets is a potential method for incorporating missing variables. Prior studies have focused upon the bias introduced by imperfect linkage. This analysis uses a case study of hepatitis C patients to estimate the net effect of statistical linkage on bias, also accounting for the potential reduction in missing variable bias. The results show that statistical linkage can reduce bias while also enabling parameter estimates to be obtained for the formerly missing variables. The usefulness of statistical linkage will vary depending upon the strength of the correlations of the missing variables with the treatment variable, as well as the outcome variable of interest.

Review of guidelines and literature for handling missing data in longitudinal clinical trials with a case study.

PubMed

Liu, M; Wei, L; Zhang, J

2006-01-01

Missing data in clinical trials are inevitable. We highlight the ICH guidelines and CPMP points to consider on missing data. Specifically, we outline how we should consider missing data issues when designing, planning and conducting studies to minimize missing data impact. We also go beyond the coverage of the above two documents, provide a more detailed review of the basic concepts of missing data and frequently used terminologies, and examples of the typical missing data mechanism, and discuss technical details and literature for several frequently used statistical methods and associated software. Finally, we provide a case study where the principles outlined in this paper are applied to one clinical program at protocol design, data analysis plan and other stages of a clinical trial.

A guide to missing data for the pediatric nephrologist.

PubMed

Larkins, Nicholas G; Craig, Jonathan C; Teixeira-Pinto, Armando

2018-03-13

Missing data is an important and common source of bias in clinical research. Readers should be alert to and consider the impact of missing data when reading studies. Beyond preventing missing data in the first place, through good study design and conduct, there are different strategies available to handle data containing missing observations. Complete case analysis is often biased unless data are missing completely at random. Better methods of handling missing data include multiple imputation and models using likelihood-based estimation. With advancing computing power and modern statistical software, these methods are within the reach of clinician-researchers under guidance of a biostatistician. As clinicians reading papers, we need to continue to update our understanding of statistical methods, so that we understand the limitations of these techniques and can critically interpret literature.

Genetic Diversity Analysis of Highly Incomplete SNP Genotype Data with Imputations: An Empirical Assessment

PubMed Central

Fu, Yong-Bi

2014-01-01

Genotyping by sequencing (GBS) recently has emerged as a promising genomic approach for assessing genetic diversity on a genome-wide scale. However, concerns are not lacking about the uniquely large unbalance in GBS genotype data. Although some genotype imputation has been proposed to infer missing observations, little is known about the reliability of a genetic diversity analysis of GBS data, with up to 90% of observations missing. Here we performed an empirical assessment of accuracy in genetic diversity analysis of highly incomplete single nucleotide polymorphism genotypes with imputations. Three large single-nucleotide polymorphism genotype data sets for corn, wheat, and rice were acquired, and missing data with up to 90% of missing observations were randomly generated and then imputed for missing genotypes with three map-independent imputation methods. Estimating heterozygosity and inbreeding coefficient from original, missing, and imputed data revealed variable patterns of bias from assessed levels of missingness and genotype imputation, but the estimation biases were smaller for missing data without genotype imputation. The estimates of genetic differentiation were rather robust up to 90% of missing observations but became substantially biased when missing genotypes were imputed. The estimates of topology accuracy for four representative samples of interested groups generally were reduced with increased levels of missing genotypes. Probabilistic principal component analysis based imputation performed better in terms of topology accuracy than those analyses of missing data without genotype imputation. These findings are not only significant for understanding the reliability of the genetic diversity analysis with respect to large missing data and genotype imputation but also are instructive for performing a proper genetic diversity analysis of highly incomplete GBS or other genotype data. PMID:24626289

Association Between Missing Posterior Teeth and Occurrence of Temporomandibular Joint Condylar Erosion: A Cone Beam Computed Tomography Study.

PubMed

Bertram, Felix; Hupp, Linus; Schnabl, Dagmar; Rudisch, Ansgar; Emshoff, Rüdiger

To determine a possible association between asymptomatic temporomandibular joint (TMJ) condylar erosion and the number of missing posterior teeth and their location, as well as the number of dental quadrants with missing posterior teeth. This case-control study involved 210 patients (male to female ratio = 98:112) aged 16-74 years, with 105 asymptomatic patients with TMJ condylar erosion and a control group of 105 patients without TMJ condylar erosion. Cone beam computed tomography images were evaluated to classify the severity of TMJ condylar erosion as grade 0 (absence of erosion), grade I (slight erosion), grade II (moderate erosion), or grade III (extensive erosion). The number of missing posterior teeth (mean ± standard deviation [SD]; 2.7 ± 2.4 vs 0.7 ± 1.2) (P < .001), number of dental quadrants with missing posterior teeth (1.5 ± 1.3 vs 0.6 ± 0.9) (P < .001), and bilateral location of missing posterior teeth (41 ± 39.0 vs 10 ± 9.5) (P < .001) were all significantly higher in patients with erosion than in those without erosion. The condylar erosion grade was significantly associated with the number of missing posterior teeth (odds ratio [OR] = 1.24; P = .006), the number of dental quadrants with missing posterior teeth (OR = 1.36; P = .006), and the bilateral occurrence of missing posterior teeth (OR = 3.03; P = .002). The findings from this study suggest a possible association between TMJ condylar erosion grades and the number of missing posterior teeth, the number of quadrants with missing posterior teeth, and the bilateral occurrence of missing posterior teeth.

Handling missing values in the MDS-UPDRS.

PubMed

Goetz, Christopher G; Luo, Sheng; Wang, Lu; Tilley, Barbara C; LaPelle, Nancy R; Stebbins, Glenn T

2015-10-01

This study was undertaken to define the number of missing values permissible to render valid total scores for each Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part. To handle missing values, imputation strategies serve as guidelines to reject an incomplete rating or create a surrogate score. We tested a rigorous, scale-specific, data-based approach to handling missing values for the MDS-UPDRS. From two large MDS-UPDRS datasets, we sequentially deleted item scores, either consistently (same items) or randomly (different items) across all subjects. Lin's Concordance Correlation Coefficient (CCC) compared scores calculated without missing values with prorated scores based on sequentially increasing missing values. The maximal number of missing values retaining a CCC greater than 0.95 determined the threshold for rendering a valid prorated score. A second confirmatory sample was selected from the MDS-UPDRS international translation program. To provide valid part scores applicable across all Hoehn and Yahr (H&Y) stages when the same items are consistently missing, one missing item from Part I, one from Part II, three from Part III, but none from Part IV can be allowed. To provide valid part scores applicable across all H&Y stages when random item entries are missing, one missing item from Part I, two from Part II, seven from Part III, but none from Part IV can be allowed. All cutoff values were confirmed in the validation sample. These analyses are useful for constructing valid surrogate part scores for MDS-UPDRS when missing items fall within the identified threshold and give scientific justification for rejecting partially completed ratings that fall below the threshold. © 2015 International Parkinson and Movement Disorder Society.

The role of trauma team leaders in missed injuries: does specialty matter?

PubMed

Leeper, W Robert; Leeper, Terrence John; Vogt, Kelly Nancy; Charyk-Stewart, Tanya; Gray, Daryl Kenneth; Parry, Neil Geordie

2013-09-01

Previous studies have identified missed injuries as a common and potentially preventable occurrence in trauma care. Several patient- and injury-related variables have been identified, which predict for missed injuries; however, differences in rate and severity of missed injuries between surgeon and nonsurgeon trauma team leaders (TTLs) have not previously been reported. A retrospective review was conducted on a random sample of 10% of all trauma patients (Injury Severity Score [ISS] > 12) from 1999 to 2009 at a Canadian Level I trauma center. Missed injuries were defined as those identified greater than 24 hours after presentation and were independently adjudicated by two reviewers. TTLs were identified as either surgeons or nonsurgeons. Of our total trauma population of 2,956 patients, 300 charts were randomly pulled for detailed review. Missed injuries occurred in 46 patients (15%). Most common missed injuries were fractures (n = 32, 70%) and thoracic injuries (n = 23, 50%). The majority of missed injuries resulted in minor morbidity with only 5 (11%) requiring operative intervention. On univariate analysis, higher ISS (p < 0.01), higher maximum Abbreviated Injury Scale (MAIS) score of the thorax (p < 0.01), and nonsurgeon TTL status were predictive of missed injuries (p = 0.02). Multivariable logistic regression revealed that, after adjustment for age, ISS, and severe head injuries, the presence of a nonsurgeon TTL was associated with an increased odds of missed injury (odds ratio, 2.15; 95% confidence interval, 1.10-4.20). Missed injuries occurred in 15% of patients. A unique finding was the increased odds of missed injury with nonsurgeon TTLs. Further research should be undertaken to explore this relationship, elucidate potential causes, and propose interventions to narrow this discrepancy between TTL provider types. Therapeutic study, level IV. Prognostic and epidemiologic study, level III.

Amplified Striatal Responses to Near-Miss Outcomes in Pathological Gamblers

PubMed Central

Sescousse, Guillaume; Janssen, Lieneke K; Hashemi, Mahur M; Timmer, Monique H M; Geurts, Dirk E M; ter Huurne, Niels P; Clark, Luke; Cools, Roshan

2016-01-01

Near-misses in gambling games are losing events that come close to a win. Near-misses were previously shown to recruit reward-related brain regions including the ventral striatum, and to invigorate gambling behavior, supposedly by fostering an illusion of control. Given that pathological gamblers are particularly vulnerable to such cognitive illusions, their persistent gambling behavior might result from an amplified striatal sensitivity to near-misses. In addition, animal studies have shown that behavioral responses to near-miss-like events are sensitive to dopamine, but this dopaminergic influence has not been tested in humans. To investigate these hypotheses, we recruited 22 pathological gamblers and 22 healthy controls who played a slot machine task delivering wins, near-misses and full-misses, inside an fMRI scanner. Each participant played the task twice, once under placebo and once under a dopamine D2 receptor antagonist (sulpiride 400 mg), in a double-blind, counter-balanced design. Participants were asked about their motivation to continue gambling throughout the task. Across all participants, near-misses elicited higher motivation to continue gambling and increased striatal responses compared with full-misses. Crucially, pathological gamblers showed amplified striatal responses to near-misses compared with controls. These group differences were not observed following win outcomes. In contrast to our hypothesis, sulpiride did not induce any reliable modulation of brain responses to near-misses. Together, our results demonstrate that pathological gamblers have amplified brain responses to near-misses, which likely contribute to their persistent gambling behavior. However, there is no evidence that these responses are influenced by dopamine. These results have implications for treatment and gambling regulation. PMID:27006113

Design, implementation and reporting strategies to reduce the instance and impact of missing patient-reported outcome (PRO) data: a systematic review

PubMed Central

Mercieca-Bebber, Rebecca; Palmer, Michael J; Brundage, Michael; Stockler, Martin R; King, Madeleine T

2016-01-01

Objectives Patient-reported outcomes (PROs) provide important information about the impact of treatment from the patients' perspective. However, missing PRO data may compromise the interpretability and value of the findings. We aimed to report: (1) a non-technical summary of problems caused by missing PRO data; and (2) a systematic review by collating strategies to: (A) minimise rates of missing PRO data, and (B) facilitate transparent interpretation and reporting of missing PRO data in clinical research. Our systematic review does not address statistical handling of missing PRO data. Data sources MEDLINE and Cumulative Index to Nursing and Allied Health Literature (CINAHL) databases (inception to 31 March 2015), and citing articles and reference lists from relevant sources. Eligibility criteria English articles providing recommendations for reducing missing PRO data rates, or strategies to facilitate transparent interpretation and reporting of missing PRO data were included. Methods 2 reviewers independently screened articles against eligibility criteria. Discrepancies were resolved with the research team. Recommendations were extracted and coded according to framework synthesis. Results 117 sources (55% discussion papers, 26% original research) met the eligibility criteria. Design and methodological strategies for reducing rates of missing PRO data included: incorporating PRO-specific information into the protocol; carefully designing PRO assessment schedules and defining termination rules; minimising patient burden; appointing a PRO coordinator; PRO-specific training for staff; ensuring PRO studies are adequately resourced; and continuous quality assurance. Strategies for transparent interpretation and reporting of missing PRO data include utilising auxiliary data to inform analysis; transparently reporting baseline PRO scores, rates and reasons for missing data; and methods for handling missing PRO data. Conclusions The instance of missing PRO data and its potential to bias clinical research can be minimised by implementing thoughtful design, rigorous methodology and transparent reporting strategies. All members of the research team have a responsibility in implementing such strategies. PMID:27311907

28 CFR 19.3 - Policy.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Administration DEPARTMENT OF JUSTICE USE OF PENALTY MAIL IN THE LOCATION AND RECOVERY OF MISSING CHILDREN § 19.3... location and recovery of missing children by maximizing the economical use of missing children photographs... the use of inserts printed with missing children photographs and biographical information has been...

Replacing missing values using trustworthy data values from web data sources

NASA Astrophysics Data System (ADS)

Izham Jaya, M.; Sidi, Fatimah; Mat Yusof, Sharmila; Suriani Affendey, Lilly; Ishak, Iskandar; Jabar, Marzanah A.

2017-09-01

In practice, collected data usually are incomplete and contains missing value. Existing approaches in managing missing values overlook the importance of trustworthy data values in replacing missing values. In view that trusted completed data is very important in data analysis, we proposed a framework of missing value replacement using trustworthy data values from web data sources. The proposed framework adopted ontology to map data values from web data sources to the incomplete dataset. As data from web is conflicting with each other, we proposed a trust score measurement based on data accuracy and data reliability. Trust score is then used to select trustworthy data values from web data sources for missing values replacement. We successfully implemented the proposed framework using financial dataset and presented the findings in this paper. From our experiment, we manage to show that replacing missing values with trustworthy data values is important especially in a case of conflicting data to solve missing values problem.

Do people treat missing information adaptively when making inferences?

PubMed

Garcia-Retamero, Rocio; Rieskamp, Jörg

2009-10-01

When making inferences, people are often confronted with situations with incomplete information. Previous research has led to a mixed picture about how people react to missing information. Options include ignoring missing information, treating it as either positive or negative, using the average of past observations for replacement, or using the most frequent observation of the available information as a placeholder. The accuracy of these inference mechanisms depends on characteristics of the environment. When missing information is uniformly distributed, it is most accurate to treat it as the average, whereas when it is negatively correlated with the criterion to be judged, treating missing information as if it were negative is most accurate. Whether people treat missing information adaptively according to the environment was tested in two studies. The results show that participants were sensitive to how missing information was distributed in an environment and most frequently selected the mechanism that was most adaptive. From these results the authors conclude that reacting to missing information in different ways is an adaptive response to environmental characteristics.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Khachatryan, Vardan

The performance of missing transverse energy reconstruction algorithms is presented by our team using√s=8 TeV proton-proton (pp) data collected with the CMS detector. Events with anomalous missing transverse energy are studied, and the performance of algorithms used to identify and remove these events is presented. The scale and resolution for missing transverse energy, including the effects of multiple pp interactions (pileup), are measured using events with an identified Z boson or isolated photon, and are found to be well described by the simulation. Novel missing transverse energy reconstruction algorithms developed specifically to mitigate the effects of large numbers of pileupmore » interactions on the missing transverse energy resolution are presented. These algorithms significantly reduce the dependence of the missing transverse energy resolution on pileup interactions. Furthermore, an algorithm that provides an estimate of the significance of the missing transverse energy is presented, which is used to estimate the compatibility of the reconstructed missing transverse energy with a zero nominal value.« less

MISSE-X: An ISS External Platform for Space Environmental Studies in the Post-Shuttle Era

NASA Technical Reports Server (NTRS)

Thibeault, Sheila A.; Cooke, Stuart A.; Ashe, Melissa P.; Saucillo, Rudolph J.; Murphy, Douglas G.; deGroh, Kim K.; Jaworske, Donald A.; Nguyen, Quang-Viet

2011-01-01

Materials International Space Station Experiment-X (MISSE-X) is a proposed International Space Station (ISS) external platform for space environmental studies designed to advance the technology readiness of materials and devices critical for future space exploration. The MISSE-X platform will expand ISS utilization by providing experimenters with unprecedented low-cost space access and return on investment (ROI). As a follow-on to the highly successful MISSE series of ISS experiments, MISSE-X will provide advances over the original MISSE configurations including incorporation of plug-and-play experiments that will minimize return mass requirements in the post-Shuttle era, improved active sensing and monitoring of the ISS external environment for better characterization of environmental effects, and expansion of the MISSE-X user community through incorporation of new, customer-desired capabilities. MISSE-X will also foster interest in science, technology, engineering, and math (STEM) in primary and secondary schools through student collaboration and participation.1,2

Strategies for Dealing with Missing Accelerometer Data.

PubMed

Stephens, Samantha; Beyene, Joseph; Tremblay, Mark S; Faulkner, Guy; Pullnayegum, Eleanor; Feldman, Brian M

2018-05-01

Missing data is a universal research problem that can affect studies examining the relationship between physical activity measured with accelerometers and health outcomes. Statistical techniques are available to deal with missing data; however, available techniques have not been synthesized. A scoping review was conducted to summarize the advantages and disadvantages of identified methods of dealing with missing data from accelerometers. Missing data poses a threat to the validity and interpretation of trials using physical activity data from accelerometry. Imputation using multiple imputation techniques is recommended to deal with missing data and improve the validity and interpretation of studies using accelerometry. Copyright © 2018 Elsevier Inc. All rights reserved.

Randomly and Non-Randomly Missing Renal Function Data in the Strong Heart Study: A Comparison of Imputation Methods

PubMed Central

Shara, Nawar; Yassin, Sayf A.; Valaitis, Eduardas; Wang, Hong; Howard, Barbara V.; Wang, Wenyu; Lee, Elisa T.; Umans, Jason G.

2015-01-01

Kidney and cardiovascular disease are widespread among populations with high prevalence of diabetes, such as American Indians participating in the Strong Heart Study (SHS). Studying these conditions simultaneously in longitudinal studies is challenging, because the morbidity and mortality associated with these diseases result in missing data, and these data are likely not missing at random. When such data are merely excluded, study findings may be compromised. In this article, a subset of 2264 participants with complete renal function data from Strong Heart Exams 1 (1989–1991), 2 (1993–1995), and 3 (1998–1999) was used to examine the performance of five methods used to impute missing data: listwise deletion, mean of serial measures, adjacent value, multiple imputation, and pattern-mixture. Three missing at random models and one non-missing at random model were used to compare the performance of the imputation techniques on randomly and non-randomly missing data. The pattern-mixture method was found to perform best for imputing renal function data that were not missing at random. Determining whether data are missing at random or not can help in choosing the imputation method that will provide the most accurate results. PMID:26414328

Randomly and Non-Randomly Missing Renal Function Data in the Strong Heart Study: A Comparison of Imputation Methods.

PubMed

Shara, Nawar; Yassin, Sayf A; Valaitis, Eduardas; Wang, Hong; Howard, Barbara V; Wang, Wenyu; Lee, Elisa T; Umans, Jason G

2015-01-01

Kidney and cardiovascular disease are widespread among populations with high prevalence of diabetes, such as American Indians participating in the Strong Heart Study (SHS). Studying these conditions simultaneously in longitudinal studies is challenging, because the morbidity and mortality associated with these diseases result in missing data, and these data are likely not missing at random. When such data are merely excluded, study findings may be compromised. In this article, a subset of 2264 participants with complete renal function data from Strong Heart Exams 1 (1989-1991), 2 (1993-1995), and 3 (1998-1999) was used to examine the performance of five methods used to impute missing data: listwise deletion, mean of serial measures, adjacent value, multiple imputation, and pattern-mixture. Three missing at random models and one non-missing at random model were used to compare the performance of the imputation techniques on randomly and non-randomly missing data. The pattern-mixture method was found to perform best for imputing renal function data that were not missing at random. Determining whether data are missing at random or not can help in choosing the imputation method that will provide the most accurate results.

Improving data sharing in research with context-free encoded missing data.

PubMed

Hoevenaar-Blom, Marieke P; Guillemont, Juliette; Ngandu, Tiia; Beishuizen, Cathrien R L; Coley, Nicola; Moll van Charante, Eric P; Andrieu, Sandrine; Kivipelto, Miia; Soininen, Hilkka; Brayne, Carol; Meiller, Yannick; Richard, Edo

2017-01-01

Lack of attention to missing data in research may result in biased results, loss of power and reduced generalizability. Registering reasons for missing values at the time of data collection, or-in the case of sharing existing data-before making data available to other teams, can save time and efforts, improve scientific value and help to prevent erroneous assumptions and biased results. To ensure that encoding of missing data is sufficient to understand the reason why data are missing, it should ideally be context-free. Therefore, 11 context-free codes of missing data were carefully designed based on three completed randomized controlled clinical trials and tested in a new randomized controlled clinical trial by an international team consisting of clinical researchers and epidemiologists with extended experience in designing and conducting trials and an Information System expert. These codes can be divided into missing due to participant and/or participation characteristics (n = 6), missing by design (n = 4), and due to a procedural error (n = 1). Broad implementation of context-free missing data encoding may enhance the possibilities of data sharing and pooling, thus allowing more powerful analyses using existing data.

Missing Value Imputation Approach for Mass Spectrometry-based Metabolomics Data.

PubMed

Wei, Runmin; Wang, Jingye; Su, Mingming; Jia, Erik; Chen, Shaoqiu; Chen, Tianlu; Ni, Yan

2018-01-12

Missing values exist widely in mass-spectrometry (MS) based metabolomics data. Various methods have been applied for handling missing values, but the selection can significantly affect following data analyses. Typically, there are three types of missing values, missing not at random (MNAR), missing at random (MAR), and missing completely at random (MCAR). Our study comprehensively compared eight imputation methods (zero, half minimum (HM), mean, median, random forest (RF), singular value decomposition (SVD), k-nearest neighbors (kNN), and quantile regression imputation of left-censored data (QRILC)) for different types of missing values using four metabolomics datasets. Normalized root mean squared error (NRMSE) and NRMSE-based sum of ranks (SOR) were applied to evaluate imputation accuracy. Principal component analysis (PCA)/partial least squares (PLS)-Procrustes analysis were used to evaluate the overall sample distribution. Student's t-test followed by correlation analysis was conducted to evaluate the effects on univariate statistics. Our findings demonstrated that RF performed the best for MCAR/MAR and QRILC was the favored one for left-censored MNAR. Finally, we proposed a comprehensive strategy and developed a public-accessible web-tool for the application of missing value imputation in metabolomics ( https://metabolomics.cc.hawaii.edu/software/MetImp/ ).

A novel application of the Intent to Attend assessment to reduce bias due to missing data in a randomized controlled clinical trial

PubMed Central

Rabideau, Dustin J; Nierenberg, Andrew A; Sylvia, Louisa G; Friedman, Edward S.; Bowden, Charles L.; Thase, Michael E.; Ketter, Terence; Ostacher, Michael J.; Reilly-Harrington, Noreen; Iosifescu, Dan V.; Calabrese, Joseph R.; Leon, Andrew C.; Schoenfeld, David A

2014-01-01

Background Missing data are unavoidable in most randomized controlled clinical trials, especially when measurements are taken repeatedly. If strong assumptions about the missing data are not accurate, crude statistical analyses are biased and can lead to false inferences. Furthermore, if we fail to measure all predictors of missing data, we may not be able to model the missing data process sufficiently. In longitudinal randomized trials, measuring a patient's intent to attend future study visits may help to address both of these problems. Leon et al. developed and included the Intent to Attend assessment in the Lithium Treatment—Moderate dose Use Study (LiTMUS), aiming to remove bias due to missing data from the primary study hypothesis [1]. Purpose The purpose of this study is to assess the performance of the Intent to Attend assessment with regard to its use in a sensitivity analysis of missing data. Methods We fit marginal models to assess whether a patient's self-rated intent predicted actual study adherence. We applied inverse probability of attrition weighting (IPAW) coupled with patient intent to assess whether there existed treatment group differences in response over time. We compared the IPAW results to those obtained using other methods. Results Patient-rated intent predicted missed study visits, even when adjusting for other predictors of missing data. On average, the hazard of retention increased by 19% for every one-point increase in intent. We also found that more severe mania, male gender, and a previously missed visit predicted subsequent absence. Although we found no difference in response between the randomized treatment groups, IPAW increased the estimated group difference over time. Limitations LiTMUS was designed to limit missed study visits, which may have attenuated the effects of adjusting for missing data. Additionally, IPAW can be less efficient and less powerful than maximum likelihood or Bayesian estimators, given that the parametric model is well-specified. Conclusions In LiTMUS, the Intent to Attend assessment predicted missed study visits. This item was incorporated into our IPAW models and helped reduce bias due to informative missing data. This analysis should both encourage and facilitate future use of the Intent to Attend assessment along with IPAW to address missing data in a randomized trial. PMID:24872362

The treatment of missing data in a large cardiovascular clinical outcomes study.

PubMed

Little, Roderick J; Wang, Julia; Sun, Xiang; Tian, Hong; Suh, Eun-Young; Lee, Michael; Sarich, Troy; Oppenheimer, Leonard; Plotnikov, Alexei; Wittes, Janet; Cook-Bruns, Nancy; Burton, Paul; Gibson, C Michael; Mohanty, Surya

2016-06-01

The potential impact of missing data on the results of clinical trials has received heightened attention recently. A National Research Council study provides recommendations for limiting missing data in clinical trial design and conduct, and principles for analysis, including the need for sensitivity analyses to assess robustness of findings to alternative assumptions about the missing data. A Food and Drug Administration advisory committee raised missing data as a serious concern in their review of results from the ATLAS ACS 2 TIMI 51 study, a large clinical trial that assessed rivaroxaban for its ability to reduce the risk of cardiovascular death, myocardial infarction or stroke in patients with acute coronary syndrome. This case study describes a variety of measures that were taken to address concerns about the missing data. A range of analyses are described to assess the potential impact of missing data on conclusions. In particular, measures of the amount of missing data are discussed, and the fraction of missing information from multiple imputation is proposed as an alternative measure. The sensitivity analysis in the National Research Council study is modified in the context of survival analysis where some individuals are lost to follow-up. The impact of deviations from ignorable censoring is assessed by differentially increasing the hazard of the primary outcome in the treatment groups and multiply imputing events between dropout and the end of the study. Tipping-point analyses are described, where the deviation from ignorable censoring that results in a reversal of significance of the treatment effect is determined. A study to determine the vital status of participants lost to follow-up was also conducted, and the results of including this additional information are assessed. Sensitivity analyses suggest that findings of the ATLAS ACS 2 TIMI 51 study are robust to missing data; this robustness is reinforced by the follow-up study, since inclusion of data from this study had little impact on the study conclusions. Missing data are a serious problem in clinical trials. The methods presented here, namely, the sensitivity analyses, the follow-up study to determine survival of missing cases, and the proposed measurement of missing data via the fraction of missing information, have potential application in other studies involving survival analysis where missing data are a concern. © The Author(s) 2016.

40 CFR 75.32 - Determination of monitor data availability for standard missing data procedures.

Code of Federal Regulations, 2011 CFR

2011-07-01

... availability for standard missing data procedures. 75.32 Section 75.32 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.32 Determination of monitor data availability for standard missing data procedures...

40 CFR 75.32 - Determination of monitor data availability for standard missing data procedures.

Code of Federal Regulations, 2014 CFR

2014-07-01

... availability for standard missing data procedures. 75.32 Section 75.32 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.32 Determination of monitor data availability for standard missing data procedures...

40 CFR 75.32 - Determination of monitor data availability for standard missing data procedures.

Code of Federal Regulations, 2013 CFR

2013-07-01

... availability for standard missing data procedures. 75.32 Section 75.32 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.32 Determination of monitor data availability for standard missing data procedures...

40 CFR 75.32 - Determination of monitor data availability for standard missing data procedures.

Code of Federal Regulations, 2010 CFR

2010-07-01

... availability for standard missing data procedures. 75.32 Section 75.32 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.32 Determination of monitor data availability for standard missing data procedures...

40 CFR 75.32 - Determination of monitor data availability for standard missing data procedures.

Code of Federal Regulations, 2012 CFR

2012-07-01

... availability for standard missing data procedures. 75.32 Section 75.32 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.32 Determination of monitor data availability for standard missing data procedures...

Integrative missing value estimation for microarray data.

PubMed

Hu, Jianjun; Li, Haifeng; Waterman, Michael S; Zhou, Xianghong Jasmine

2006-10-12

Missing value estimation is an important preprocessing step in microarray analysis. Although several methods have been developed to solve this problem, their performance is unsatisfactory for datasets with high rates of missing data, high measurement noise, or limited numbers of samples. In fact, more than 80% of the time-series datasets in Stanford Microarray Database contain less than eight samples. We present the integrative Missing Value Estimation method (iMISS) by incorporating information from multiple reference microarray datasets to improve missing value estimation. For each gene with missing data, we derive a consistent neighbor-gene list by taking reference data sets into consideration. To determine whether the given reference data sets are sufficiently informative for integration, we use a submatrix imputation approach. Our experiments showed that iMISS can significantly and consistently improve the accuracy of the state-of-the-art Local Least Square (LLS) imputation algorithm by up to 15% improvement in our benchmark tests. We demonstrated that the order-statistics-based integrative imputation algorithms can achieve significant improvements over the state-of-the-art missing value estimation approaches such as LLS and is especially good for imputing microarray datasets with a limited number of samples, high rates of missing data, or very noisy measurements. With the rapid accumulation of microarray datasets, the performance of our approach can be further improved by incorporating larger and more appropriate reference datasets.

Relationship of Number of Missing Teeth to Hip Fracture in Elderly Patients: A Cohort Pilot Study.

PubMed

Priebe, Jennifer; Wermers, Robert A; Sems, Stephen A; Viozzi, Christopher F; Koka, Sreenivas

2017-09-15

To determine the relationship between the number of missing natural teeth or remaining natural teeth and osteoporotic hip fracture in elderly patients and to determine the relationship between the number of missing teeth or remaining teeth and osteoporotic fracture risk assessment (FRAX) probability. Number of missing teeth was determined by clinical oral exam on a total of 100 subjects, 50 with hip fractures and 50 without. Ten-year fracture risk and hip fracture risk probabilities were calculated using the FRAX tool. Statistical analyses were performed to determine strength of associations between number of missing natural teeth and likelihood of experiencing a fracture. Degree of correlation between number of missing natural teeth and FRAX probabilities were calculated. There appears to be an association between the number of missing natural teeth and hip fractures. For every 5-tooth increase in the number of missing teeth, the likelihood of being a subject in the hip fracture group increased by 26%. Number of missing natural teeth was positively correlated with FRAX overall fracture and hip fracture probability. Number of missing natural teeth may be a valuable tool to assist members of medical and dental teams in identifying patients with higher FRAX scores and higher likelihood of experiencing a hip fracture. Additional research is necessary to validate these findings. © 2017 by the American College of Prosthodontists.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bercovici, B.; Wassermann, M.; Cucos, S.

Polychlorinated biphenyls and some organochlorine insecticides (DDT isomers and their metabolites, indane (..gamma..-BHC), dieldrin, heptachlor epoxide) were assessed in the serum of 17 women with recent missed abortions, 7 women who experienced one or several missed abortions in their past, and 7 women with normal, second trimester pregnancy. Fifty-three percent of the cases of recent missed abortion had PCB serum levels higher than the mean plus two standard deviations of the control group. The mean PCB serum level in women with recent missed abortion and relatively high PCB serum levels was significantly different from that of the control group (103.04more » versus 20.69 ppb,P<0.001). The mean PCB serum level of the former missed abortions group was also significantly different from that of the control group (82.00 versus 20.69 ppb, P<0.001). The quantity of the higher chlorinated biphenyl homologues (penta- and hexachlorobiphenyls) was increased in the high PCB level, missed abortion group and in the former missed abortion group, while the lower chlorinated biphenyl homologues were decreased in these groups in comparsion with the control group. The fact that the former missed abortion group showed increased PCB serum levels similar to those found in the high PCB level, recent missed abortion group confirms the existence of an association between relatively high PCB serum levels and the occurance of missed abortion. (JMT)« less

Shrinkage regression-based methods for microarray missing value imputation.

PubMed

Wang, Hsiuying; Chiu, Chia-Chun; Wu, Yi-Ching; Wu, Wei-Sheng

2013-01-01

Missing values commonly occur in the microarray data, which usually contain more than 5% missing values with up to 90% of genes affected. Inaccurate missing value estimation results in reducing the power of downstream microarray data analyses. Many types of methods have been developed to estimate missing values. Among them, the regression-based methods are very popular and have been shown to perform better than the other types of methods in many testing microarray datasets. To further improve the performances of the regression-based methods, we propose shrinkage regression-based methods. Our methods take the advantage of the correlation structure in the microarray data and select similar genes for the target gene by Pearson correlation coefficients. Besides, our methods incorporate the least squares principle, utilize a shrinkage estimation approach to adjust the coefficients of the regression model, and then use the new coefficients to estimate missing values. Simulation results show that the proposed methods provide more accurate missing value estimation in six testing microarray datasets than the existing regression-based methods do. Imputation of missing values is a very important aspect of microarray data analyses because most of the downstream analyses require a complete dataset. Therefore, exploring accurate and efficient methods for estimating missing values has become an essential issue. Since our proposed shrinkage regression-based methods can provide accurate missing value estimation, they are competitive alternatives to the existing regression-based methods.

Effects of correcting missing daily feed intake values on the genetic parameters and estimated breeding values for feeding traits in pigs.

PubMed

Ito, Tetsuya; Fukawa, Kazuo; Kamikawa, Mai; Nikaidou, Satoshi; Taniguchi, Masaaki; Arakawa, Aisaku; Tanaka, Genki; Mikawa, Satoshi; Furukawa, Tsutomu; Hirose, Kensuke

2018-01-01

Daily feed intake (DFI) is an important consideration for improving feed efficiency, but measurements using electronic feeder systems contain many missing and incorrect values. Therefore, we evaluated three methods for correcting missing DFI data (quadratic, orthogonal polynomial, and locally weighted (Loess) regression equations) and assessed the effects of these missing values on the genetic parameters and the estimated breeding values (EBV) for feeding traits. DFI records were obtained from 1622 Duroc pigs, comprising 902 individuals without missing DFI and 720 individuals with missing DFI. The Loess equation was the most suitable method for correcting the missing DFI values in 5-50% randomly deleted datasets among the three equations. Both variance components and heritability for the average DFI (ADFI) did not change because of the missing DFI proportion and Loess correction. In terms of rank correlation and information criteria, Loess correction improved the accuracy of EBV for ADFI compared to randomly deleted cases. These findings indicate that the Loess equation is useful for correcting missing DFI values for individual pigs and that the correction of missing DFI values could be effective for the estimation of breeding values and genetic improvement using EBV for feeding traits. © 2017 The Authors. Animal Science Journal published by John Wiley & Sons Australia, Ltd on behalf of Japanese Society of Animal Science.

Autoregressive-model-based missing value estimation for DNA microarray time series data.

PubMed

Choong, Miew Keen; Charbit, Maurice; Yan, Hong

2009-01-01

Missing value estimation is important in DNA microarray data analysis. A number of algorithms have been developed to solve this problem, but they have several limitations. Most existing algorithms are not able to deal with the situation where a particular time point (column) of the data is missing entirely. In this paper, we present an autoregressive-model-based missing value estimation method (ARLSimpute) that takes into account the dynamic property of microarray temporal data and the local similarity structures in the data. ARLSimpute is especially effective for the situation where a particular time point contains many missing values or where the entire time point is missing. Experiment results suggest that our proposed algorithm is an accurate missing value estimator in comparison with other imputation methods on simulated as well as real microarray time series datasets.

The Strengths and Limitations of South Africa's Search for Apartheid-Era Missing Persons.

PubMed

Aronson, Jay D

2011-07-01

This article examines efforts to account for missing persons from the apartheid era in South Africa by family members, civil society organizations and the current government's Missing Persons Task Team, which emerged out of the Truth and Reconciliation Commission process. It focuses on how missing persons have been officially defined in the South African context and the extent to which the South African government is able to address the current needs and desires of relatives of the missing. I make two main arguments: that family members ought to have an active role in shaping the initiatives and institutions that seek to resolve the fate of missing people, and that the South African government ought to take a more holistic 'grave-to-grave' approach to the process of identifying, returning and reburying the remains of the missing.

Statistical primer: how to deal with missing data in scientific research?

PubMed

Papageorgiou, Grigorios; Grant, Stuart W; Takkenberg, Johanna J M; Mokhles, Mostafa M

2018-05-10

Missing data are a common challenge encountered in research which can compromise the results of statistical inference when not handled appropriately. This paper aims to introduce basic concepts of missing data to a non-statistical audience, list and compare some of the most popular approaches for handling missing data in practice and provide guidelines and recommendations for dealing with and reporting missing data in scientific research. Complete case analysis and single imputation are simple approaches for handling missing data and are popular in practice, however, in most cases they are not guaranteed to provide valid inferences. Multiple imputation is a robust and general alternative which is appropriate for data missing at random, surpassing the disadvantages of the simpler approaches, but should always be conducted with care. The aforementioned approaches are illustrated and compared in an example application using Cox regression.

Sleepy driver near-misses may predict accident risks.

PubMed

Powell, Nelson B; Schechtman, Kenneth B; Riley, Robert W; Guilleminault, Christian; Chiang, Rayleigh Ping-ying; Weaver, Edward M

2007-03-01

To quantify the prevalence of self-reported near-miss sleepy driving accidents and their association with self-reported actual driving accidents. A prospective cross-sectional internet-linked survey on driving behaviors. Dateline NBC News website. Results are given on 35,217 (88% of sample) individuals with a mean age of 37.2 +/- 13 years, 54.8% women, and 87% white. The risk of at least one accident increased monotonically from 23.2% if there were no near-miss sleepy accidents to 44.5% if there were > or = 4 near-miss sleepy accidents (P < 0.0001). After covariate adjustments, subjects who reported at least one near-miss sleepy accident were 1.13 (95% CI, 1.10 to 1.16) times as likely to have reported at least one actual accident as subjects reporting no near-miss sleepy accidents (P < 0.0001). The odds of reporting at least one actual accident in those reporting > or = 4 near-miss sleepy accidents as compared to those reporting no near-miss sleepy accidents was 1.87 (95% CI, 1.64 to 2.14). Furthermore, after adjustments, the summary Epworth Sleepiness Scale (ESS) score had an independent association with having a near-miss or actual accident. An increase of 1 unit of ESS was associated with a covariate adjusted 4.4% increase of having at least one accident (P < 0.0001). A statistically significant dose-response was seen between the numbers of self-reported sleepy near-miss accidents and an actual accident. These findings suggest that sleepy near-misses may be dangerous precursors to an actual accident.

Missing CD4+ cell response in randomized clinical trials of maraviroc and dolutegravir.

PubMed

Cuffe, Robert; Barnett, Carly; Granier, Catherine; Machida, Mitsuaki; Wang, Cunshan; Roger, James

2015-10-01

Missing data can compromise inferences from clinical trials, yet the topic has received little attention in the clinical trial community. Shortcomings in commonly used methods used to analyze studies with missing data (complete case, last- or baseline-observation carried forward) have been highlighted in a recent Food and Drug Administration-sponsored report. This report recommends how to mitigate the issues associated with missing data. We present an example of the proposed concepts using data from recent clinical trials. CD4+ cell count data from the previously reported SINGLE and MOTIVATE studies of dolutegravir and maraviroc were analyzed using a variety of statistical methods to explore the impact of missing data. Four methodologies were used: complete case analysis, simple imputation, mixed models for repeated measures, and multiple imputation. We compared the sensitivity of conclusions to the volume of missing data and to the assumptions underpinning each method. Rates of missing data were greater in the MOTIVATE studies (35%-68% premature withdrawal) than in SINGLE (12%-20%). The sensitivity of results to assumptions about missing data was related to volume of missing data. Estimates of treatment differences by various analysis methods ranged across a 61 cells/mm3 window in MOTIVATE and a 22 cells/mm3 window in SINGLE. Where missing data are anticipated, analyses require robust statistical and clinical debate of the necessary but unverifiable underlying statistical assumptions. Multiple imputation makes these assumptions transparent, can accommodate a broad range of scenarios, and is a natural analysis for clinical trials in HIV with missing data.

Modeling Achievement Trajectories when Attrition Is Informative

ERIC Educational Resources Information Center

Feldman, Betsy J.; Rabe-Hesketh, Sophia

2012-01-01

In longitudinal education studies, assuming that dropout and missing data occur completely at random is often unrealistic. When the probability of dropout depends on covariates and observed responses (called "missing at random" [MAR]), or on values of responses that are missing (called "informative" or "not missing at random" [NMAR]),…

Girls' Portraits of Desire: Picturing a Missing Discourse

ERIC Educational Resources Information Center

Allen, Louisa

2013-01-01

This paper revisits the missing discourse of female desire [Fine, M. 1988. Sexuality, schooling and adolescent females: The missing discourse of desire. "Harvard Educational Review" 58, no. 1: 29-53] in secondary schools. Instead of echoing previous studies that have documented how female desire is missing, this research starts from the…

5 CFR 1651.16 - Missing and unknown beneficiaries.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 5 Administrative Personnel 3 2012-01-01 2012-01-01 false Missing and unknown beneficiaries. 1651... § 1651.16 Missing and unknown beneficiaries. (a) Locate and identify beneficiaries. (1) The TSP record... one or more beneficiaries (and not all) appear to be missing, payment of part of the participant's...

5 CFR 1651.16 - Missing and unknown beneficiaries.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 5 Administrative Personnel 3 2013-01-01 2013-01-01 false Missing and unknown beneficiaries. 1651... § 1651.16 Missing and unknown beneficiaries. (a) Locate and identify beneficiaries. (1) The TSP record... one or more beneficiaries (and not all) appear to be missing, payment of part of the participant's...

5 CFR 1651.16 - Missing and unknown beneficiaries.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 5 Administrative Personnel 3 2010-01-01 2010-01-01 false Missing and unknown beneficiaries. 1651... § 1651.16 Missing and unknown beneficiaries. (a) Locate and identify beneficiaries. (1) The TSP record... one or more beneficiaries (and not all) appear to be missing, payment of part of the participant's...

5 CFR 1651.16 - Missing and unknown beneficiaries.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 5 Administrative Personnel 3 2011-01-01 2011-01-01 false Missing and unknown beneficiaries. 1651... § 1651.16 Missing and unknown beneficiaries. (a) Locate and identify beneficiaries. (1) The TSP record... one or more beneficiaries (and not all) appear to be missing, payment of part of the participant's...

5 CFR 1651.16 - Missing and unknown beneficiaries.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 5 Administrative Personnel 3 2014-01-01 2014-01-01 false Missing and unknown beneficiaries. 1651... § 1651.16 Missing and unknown beneficiaries. (a) Locate and identify beneficiaries. (1) The TSP record... one or more beneficiaries (and not all) appear to be missing, payment of part of the participant's...

Methods for Mediation Analysis with Missing Data

ERIC Educational Resources Information Center

Zhang, Zhiyong; Wang, Lijuan

2013-01-01

Despite wide applications of both mediation models and missing data techniques, formal discussion of mediation analysis with missing data is still rare. We introduce and compare four approaches to dealing with missing data in mediation analysis including list wise deletion, pairwise deletion, multiple imputation (MI), and a two-stage maximum…

40 CFR 98.275 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... for estimating missing data. A complete record of all measured parameters used in the GHG emissions... substitute data value for the missing parameter shall be used in the calculations, according to the...

40 CFR 98.365 - Procedures for estimating missing data.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Procedures for estimating missing data... estimating missing data. (a) A complete record of all measured parameters used in the GHG emissions... substitute data value for the missing parameter shall be used in the calculations, according to the...

40 CFR 98.435 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... Gases Contained in Pre-Charged Equipment or Closed-Cell Foams § 98.435 Procedures for estimating missing data. Procedures for estimating missing data are not provided for importers and exporters of...

40 CFR 98.365 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... estimating missing data. (a) A complete record of all measured parameters used in the GHG emissions... substitute data value for the missing parameter shall be used in the calculations, according to the...

40 CFR 98.175 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... unavailable, a substitute data value for the missing parameter shall be used in the calculations as specified...

40 CFR 98.345 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... for estimating missing data. A complete record of all measured parameters used in the GHG emissions... substitute data value for the missing parameter shall be used in the calculations, according to the...

40 CFR 98.465 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... estimating missing data. (a) A complete record of all measured parameters used in the GHG emissions... substitute data value for the missing parameter shall be used in the calculations, in accordance with...

40 CFR 98.355 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... for estimating missing data. A complete record of all measured parameters used in the GHG emissions... substitute data value for the missing parameter must be used in the calculations, according to the following...

40 CFR 98.455 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... § 98.455 Procedures for estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations is required. Replace missing data, if needed, based on data from...

40 CFR 98.435 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... Gases Contained in Pre-Charged Equipment or Closed-Cell Foams § 98.435 Procedures for estimating missing data. Procedures for estimating missing data are not provided for importers and exporters of...

40 CFR 98.215 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... for estimating missing data. (a) A complete record of all measured parameters used in the GHG... unavailable, a substitute data value for the missing parameter shall be used in the calculations as specified...

40 CFR 98.55 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... substitute data value for the missing parameter shall be used in the calculations as specified in paragraphs...

40 CFR 98.155 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... Procedures for estimating missing data. (a) A complete record of all measured parameters used in the GHG...), a substitute data value for the missing parameter shall be used in the calculations, according to...

40 CFR 98.125 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... estimating missing data. (a) A complete record of all measured parameters used in the GHG emissions... unavailable, a substitute data value for the missing parameter must be used in the calculations as specified...

40 CFR 98.265 - Procedures for estimating missing data.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... unavailable, a substitute data value for the missing parameter shall be used in the calculations as specified...

40 CFR 98.175 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... unavailable, a substitute data value for the missing parameter shall be used in the calculations as specified...

40 CFR 98.125 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... estimating missing data. (a) A complete record of all measured parameters used in the GHG emissions... unavailable, a substitute data value for the missing parameter must be used in the calculations as specified...

40 CFR 98.275 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... for estimating missing data. A complete record of all measured parameters used in the GHG emissions... substitute data value for the missing parameter shall be used in the calculations, according to the...

40 CFR 98.215 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... for estimating missing data. (a) A complete record of all measured parameters used in the GHG... unavailable, a substitute data value for the missing parameter shall be used in the calculations as specified...

40 CFR 98.345 - Procedures for estimating missing data.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Procedures for estimating missing data... for estimating missing data. A complete record of all measured parameters used in the GHG emissions... substitute data value for the missing parameter shall be used in the calculations, according to the...

40 CFR 98.345 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... for estimating missing data. A complete record of all measured parameters used in the GHG emissions... substitute data value for the missing parameter shall be used in the calculations, according to the...

40 CFR 98.155 - Procedures for estimating missing data.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Procedures for estimating missing data... Procedures for estimating missing data. (a) A complete record of all measured parameters used in the GHG...), a substitute data value for the missing parameter shall be used in the calculations, according to...

40 CFR 75.46 - Missing data substitution criteria.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 17 2013-07-01 2013-07-01 false Missing data substitution criteria. 75... (CONTINUED) CONTINUOUS EMISSION MONITORING Alternative Monitoring Systems § 75.46 Missing data substitution criteria. The owner or operator shall demonstrate that all missing data can be accounted for in a manner...

40 CFR 98.115 - Procedures for estimating missing data.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... unavailable, a substitute data value for the missing parameter shall be used in the calculations as specified...

40 CFR 98.325 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... estimating missing data. (a) A complete record of all measured parameters used in the GHG emissions... substitute data value for the missing parameter shall be used in the calculations, in accordance with...

40 CFR 98.175 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... unavailable, a substitute data value for the missing parameter shall be used in the calculations as specified...

40 CFR 98.215 - Procedures for estimating missing data.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Procedures for estimating missing data... for estimating missing data. (a) A complete record of all measured parameters used in the GHG... unavailable, a substitute data value for the missing parameter shall be used in the calculations as specified...

40 CFR 98.35 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... Procedures for estimating missing data. Whenever a quality-assured value of a required parameter is... substitute data value for the missing parameter shall be used in the calculations. (a) For all units subject...

40 CFR 75.46 - Missing data substitution criteria.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 17 2014-07-01 2014-07-01 false Missing data substitution criteria. 75... (CONTINUED) CONTINUOUS EMISSION MONITORING Alternative Monitoring Systems § 75.46 Missing data substitution criteria. The owner or operator shall demonstrate that all missing data can be accounted for in a manner...

40 CFR 98.55 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... substitute data value for the missing parameter shall be used in the calculations as specified in paragraphs...

40 CFR 75.36 - Missing data procedures for heat input rate determinations.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 16 2011-07-01 2011-07-01 false Missing data procedures for heat input... (CONTINUED) AIR PROGRAMS (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.36 Missing data procedures for heat input rate determinations. (a) When hourly heat input rate is...

40 CFR 98.325 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... estimating missing data. (a) A complete record of all measured parameters used in the GHG emissions... substitute data value for the missing parameter shall be used in the calculations, in accordance with...

40 CFR 75.46 - Missing data substitution criteria.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 16 2011-07-01 2011-07-01 false Missing data substitution criteria. 75... (CONTINUED) CONTINUOUS EMISSION MONITORING Alternative Monitoring Systems § 75.46 Missing data substitution criteria. The owner or operator shall demonstrate that all missing data can be accounted for in a manner...

40 CFR 98.275 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... for estimating missing data. A complete record of all measured parameters used in the GHG emissions... substitute data value for the missing parameter shall be used in the calculations, according to the...

40 CFR 98.215 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... for estimating missing data. (a) A complete record of all measured parameters used in the GHG... unavailable, a substitute data value for the missing parameter shall be used in the calculations as specified...

40 CFR 98.435 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... Gases Contained in Pre-Charged Equipment or Closed-Cell Foams § 98.435 Procedures for estimating missing data. Procedures for estimating missing data are not provided for importers and exporters of...

40 CFR 98.355 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... for estimating missing data. A complete record of all measured parameters used in the GHG emissions... substitute data value for the missing parameter must be used in the calculations, according to the following...

40 CFR 98.275 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... for estimating missing data. A complete record of all measured parameters used in the GHG emissions... substitute data value for the missing parameter shall be used in the calculations, according to the...

40 CFR 98.35 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... Procedures for estimating missing data. Whenever a quality-assured value of a required parameter is... substitute data value for the missing parameter shall be used in the calculations. (a) For all units subject...

40 CFR 98.155 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... Procedures for estimating missing data. (a) A complete record of all measured parameters used in the GHG...), a substitute data value for the missing parameter shall be used in the calculations, according to...

40 CFR 98.305 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... Use § 98.305 Procedures for estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations is required. Replace missing data, if needed, based on data from...

40 CFR 98.305 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... Use § 98.305 Procedures for estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations is required. Replace missing data, if needed, based on data from...

40 CFR 98.35 - Procedures for estimating missing data.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Procedures for estimating missing data... Procedures for estimating missing data. Whenever a quality-assured value of a required parameter is... substitute data value for the missing parameter shall be used in the calculations. (a) For all units subject...

40 CFR 98.435 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... Gases Contained in Pre-Charged Equipment or Closed-Cell Foams § 98.435 Procedures for estimating missing data. Procedures for estimating missing data are not provided for importers and exporters of...

40 CFR 98.455 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... § 98.455 Procedures for estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations is required. Replace missing data, if needed, based on data from...

40 CFR 98.455 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... § 98.455 Procedures for estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations is required. Replace missing data, if needed, based on data from...

40 CFR 75.46 - Missing data substitution criteria.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 17 2012-07-01 2012-07-01 false Missing data substitution criteria. 75... (CONTINUED) CONTINUOUS EMISSION MONITORING Alternative Monitoring Systems § 75.46 Missing data substitution criteria. The owner or operator shall demonstrate that all missing data can be accounted for in a manner...

40 CFR 98.305 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... Use § 98.305 Procedures for estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations is required. Replace missing data, if needed, based on data from...

40 CFR 98.365 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... estimating missing data. (a) A complete record of all measured parameters used in the GHG emissions... substitute data value for the missing parameter shall be used in the calculations, according to the...

40 CFR 98.35 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... Procedures for estimating missing data. Whenever a quality-assured value of a required parameter is... substitute data value for the missing parameter shall be used in the calculations. (a) For all units subject...

40 CFR 98.65 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... substitute data value for the missing parameter shall be used in the calculations, according to the following...

40 CFR 98.65 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... substitute data value for the missing parameter shall be used in the calculations, according to the following...

40 CFR 98.115 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... unavailable, a substitute data value for the missing parameter shall be used in the calculations as specified...

40 CFR 75.36 - Missing data procedures for heat input rate determinations.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 17 2014-07-01 2014-07-01 false Missing data procedures for heat input... (CONTINUED) AIR PROGRAMS (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.36 Missing data procedures for heat input rate determinations. (a) When hourly heat input rate is...

40 CFR 98.115 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... unavailable, a substitute data value for the missing parameter shall be used in the calculations as specified...

40 CFR 75.46 - Missing data substitution criteria.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 16 2010-07-01 2010-07-01 false Missing data substitution criteria. 75... (CONTINUED) CONTINUOUS EMISSION MONITORING Alternative Monitoring Systems § 75.46 Missing data substitution criteria. The owner or operator shall demonstrate that all missing data can be accounted for in a manner...

40 CFR 75.39 - Missing data procedures for sorbent trap monitoring systems.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 16 2010-07-01 2010-07-01 false Missing data procedures for sorbent... (CONTINUED) AIR PROGRAMS (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.39 Missing data procedures for sorbent trap monitoring systems. (a) If a primary sorbent trap...

40 CFR 98.115 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... unavailable, a substitute data value for the missing parameter shall be used in the calculations as specified...

40 CFR 98.225 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... substitute data value for the missing parameter shall be used in the calculations as specified in paragraphs...

40 CFR 98.175 - Procedures for estimating missing data.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... unavailable, a substitute data value for the missing parameter shall be used in the calculations as specified...

40 CFR 98.115 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... unavailable, a substitute data value for the missing parameter shall be used in the calculations as specified...

40 CFR 98.125 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... estimating missing data. (a) A complete record of all measured parameters used in the GHG emissions... unavailable, a substitute data value for the missing parameter must be used in the calculations as specified...

40 CFR 98.355 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... for estimating missing data. A complete record of all measured parameters used in the GHG emissions... substitute data value for the missing parameter must be used in the calculations, according to the following...

40 CFR 98.305 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... Use § 98.305 Procedures for estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations is required. Replace missing data, if needed, based on data from...

40 CFR 98.465 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... estimating missing data. (a) A complete record of all measured parameters used in the GHG emissions... substitute data value for the missing parameter shall be used in the calculations, in accordance with...

40 CFR 75.36 - Missing data procedures for heat input rate determinations.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 17 2013-07-01 2013-07-01 false Missing data procedures for heat input... (CONTINUED) AIR PROGRAMS (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.36 Missing data procedures for heat input rate determinations. (a) When hourly heat input rate is...

40 CFR 98.325 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... estimating missing data. (a) A complete record of all measured parameters used in the GHG emissions... substitute data value for the missing parameter shall be used in the calculations, in accordance with...

40 CFR 98.365 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... estimating missing data. (a) A complete record of all measured parameters used in the GHG emissions... substitute data value for the missing parameter shall be used in the calculations, according to the...

40 CFR 98.465 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... estimating missing data. (a) A complete record of all measured parameters used in the GHG emissions... substitute data value for the missing parameter shall be used in the calculations, in accordance with...

40 CFR 98.225 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... substitute data value for the missing parameter shall be used in the calculations as specified in paragraphs...

40 CFR 98.345 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... for estimating missing data. A complete record of all measured parameters used in the GHG emissions... substitute data value for the missing parameter shall be used in the calculations, according to the...

40 CFR 98.65 - Procedures for estimating missing data.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... substitute data value for the missing parameter shall be used in the calculations, according to the following...

40 CFR 98.125 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... estimating missing data. (a) A complete record of all measured parameters used in the GHG emissions... unavailable, a substitute data value for the missing parameter must be used in the calculations as specified...

40 CFR 98.55 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... substitute data value for the missing parameter shall be used in the calculations as specified in paragraphs...

40 CFR 98.155 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... Procedures for estimating missing data. (a) A complete record of all measured parameters used in the GHG...), a substitute data value for the missing parameter shall be used in the calculations, according to...

40 CFR 98.35 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... Procedures for estimating missing data. Whenever a quality-assured value of a required parameter is... substitute data value for the missing parameter shall be used in the calculations. (a) For all units subject...

40 CFR 98.55 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... substitute data value for the missing parameter shall be used in the calculations as specified in paragraphs...

40 CFR 98.65 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... substitute data value for the missing parameter shall be used in the calculations, according to the following...

40 CFR 98.265 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... substitute data value for the missing parameter must be used in the calculations as specified in paragraphs...

40 CFR 98.355 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... for estimating missing data. A complete record of all measured parameters used in the GHG emissions... substitute data value for the missing parameter must be used in the calculations, according to the following...

40 CFR 98.345 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... for estimating missing data. A complete record of all measured parameters used in the GHG emissions... substitute data value for the missing parameter shall be used in the calculations, according to the...

40 CFR 98.215 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... for estimating missing data. (a) A complete record of all measured parameters used in the GHG... unavailable, a substitute data value for the missing parameter shall be used in the calculations as specified...

40 CFR 98.325 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... estimating missing data. (a) A complete record of all measured parameters used in the GHG emissions... substitute data value for the missing parameter shall be used in the calculations, in accordance with...

40 CFR 75.36 - Missing data procedures for heat input rate determinations.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 16 2010-07-01 2010-07-01 false Missing data procedures for heat input... (CONTINUED) AIR PROGRAMS (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.36 Missing data procedures for heat input rate determinations. (a) When hourly heat input rate is...

40 CFR 75.38 - Standard missing data procedures for Hg CEMS.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 16 2010-07-01 2010-07-01 false Standard missing data procedures for...) AIR PROGRAMS (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.38 Standard missing data procedures for Hg CEMS. (a) Once 720 quality assured monitor operating hours of Hg...

40 CFR 75.36 - Missing data procedures for heat input rate determinations.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 17 2012-07-01 2012-07-01 false Missing data procedures for heat input... (CONTINUED) AIR PROGRAMS (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.36 Missing data procedures for heat input rate determinations. (a) When hourly heat input rate is...

40 CFR 98.465 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... estimating missing data. (a) A complete record of all measured parameters used in the GHG emissions... substitute data value for the missing parameter shall be used in the calculations, in accordance with...

40 CFR 98.175 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... unavailable, a substitute data value for the missing parameter shall be used in the calculations as specified...

40 CFR 98.225 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... substitute data value for the missing parameter shall be used in the calculations as specified in paragraphs...

40 CFR 98.155 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... Procedures for estimating missing data. (a) A complete record of all measured parameters used in the GHG...), a substitute data value for the missing parameter shall be used in the calculations, according to...

40 CFR 98.65 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... substitute data value for the missing parameter shall be used in the calculations, according to the following...

40 CFR 98.225 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... substitute data value for the missing parameter shall be used in the calculations as specified in paragraphs...

40 CFR 98.455 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... § 98.455 Procedures for estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations is required. Replace missing data, if needed, based on data from...

40 CFR 98.365 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... estimating missing data. (a) A complete record of all measured parameters used in the GHG emissions... substitute data value for the missing parameter shall be used in the calculations, according to the...

Near-miss incident management in the chemical process industry.

PubMed

Phimister, James R; Oktem, Ulku; Kleindorfer, Paul R; Kunreuther, Howard

2003-06-01

This article provides a systematic framework for the analysis and improvement of near-miss programs in the chemical process industries. Near-miss programs improve corporate environmental, health, and safety (EHS) performance through the identification and management of near misses. Based on more than 100 interviews at 20 chemical and pharmaceutical facilities, a seven-stage framework has been developed and is presented herein. The framework enables sites to analyze their own near-miss programs, identify weak management links, and implement systemwide improvements.

Estimated Environmental Exposures for MISSE-3 and MISSE-4

NASA Technical Reports Server (NTRS)

Finckenor, Miria M.; Pippin, Gary; Kinard, William H.

2008-01-01

Describes the estimated environmental exposure for MISSE-2 and MISSE-4. These test beds, attached to the outside of the International Space Station, were planned for 3 years of exposure. This was changed to 1 year after MISSE-1 and -2 were in space for 4 years. MISSE-3 and -4 operate in a low Earth orbit space environment, which exposes them to a variety of assaults including atomic oxygen, ultraviolet radiation, particulate radiation, thermal cycling, and meteoroid/space debris impact, as well as contamination associated with proximity to an active space station. Measurements and determinations of atomic oxygen fluences, solar UV exposure levels, molecular contamination levels, and particulate radiation are included.

Warnings reduce false memories for missing aspects of events.

PubMed

Gerrie, Matthew P; Garry, Maryanne

2011-01-01

When people see movies with some parts missing, they falsely recognize many of the missing parts later. In two experiments, we examined the effect of warnings on people's false memories for these parts. In Experiment 1, warning subjects about false recognition before the movie (forewarnings) reduced false recognition, but warning them after the movie (postwarnings) reduced false recognition to a lesser extent. In Experiment 2, the effect of the warnings depended on the nature of the missing parts. Forewarnings were more effective than postwarnings in reducing false recognition of missing noncrucial parts, but forewarnings and postwarnings were similarly effective in reducing false recognition of crucial missing parts. We use the source monitoring framework to explain our results.

Strategies for dealing with missing data in clinical trials: from design to analysis.

PubMed

Dziura, James D; Post, Lori A; Zhao, Qing; Fu, Zhixuan; Peduzzi, Peter

2013-09-01

Randomized clinical trials are the gold standard for evaluating interventions as randomized assignment equalizes known and unknown characteristics between intervention groups. However, when participants miss visits, the ability to conduct an intent-to-treat analysis and draw conclusions about a causal link is compromised. As guidance to those performing clinical trials, this review is a non-technical overview of the consequences of missing data and a prescription for its treatment beyond the typical analytic approaches to the entire research process. Examples of bias from incorrect analysis with missing data and discussion of the advantages/disadvantages of analytic methods are given. As no single analysis is definitive when missing data occurs, strategies for its prevention throughout the course of a trial are presented. We aim to convey an appreciation for how missing data influences results and an understanding of the need for careful consideration of missing data during the design, planning, conduct, and analytic stages.

Best practices for missing data management in counseling psychology.

PubMed

Schlomer, Gabriel L; Bauman, Sheri; Card, Noel A

2010-01-01

This article urges counseling psychology researchers to recognize and report how missing data are handled, because consumers of research cannot accurately interpret findings without knowing the amount and pattern of missing data or the strategies that were used to handle those data. Patterns of missing data are reviewed, and some of the common strategies for dealing with them are described. The authors provide an illustration in which data were simulated and evaluate 3 methods of handling missing data: mean substitution, multiple imputation, and full information maximum likelihood. Results suggest that mean substitution is a poor method for handling missing data, whereas both multiple imputation and full information maximum likelihood are recommended alternatives to this approach. The authors suggest that researchers fully consider and report the amount and pattern of missing data and the strategy for handling those data in counseling psychology research and that editors advise researchers of this expectation.

Prevalence of and antecedents to dementia-related missing incidents in the community.

PubMed

Bowen, Mary Elizabeth; McKenzie, Barbara; Steis, Melinda; Rowe, Meredeth

2011-01-01

The primary aim of this study is to examine the prevalence of and antecedents to missing incidents among community-dwelling persons with dementia. This prospective study used mailed surveys and telephone interviews. The prevalence of having any incident was 0.46/year; the overall prevalence for missing incidents in this study was 0.65/year. Missing incidents had few antecedents and occurred largely when persons with dementia were performing everyday activities that they normally completed without incident. Given that a missing incident is relatively common among persons with dementia, health care professionals should assist caregivers with a missing incident plan early in the disease process. Also, as missing persons are found by persons other than the caregiver and caregivers underutilize identification devices, health care professionals may recommend the use of identification devices to facilitate a safe return. Copyright © 2011 S. Karger AG, Basel.

Part Marking and Identification Materials on MISSE

NASA Technical Reports Server (NTRS)

Finckenor, Miria M.; Roxby, Donald L.

2008-01-01

Many different spacecraft materials were flown as part of the Materials on International Space Station Experiment (MISSE), including several materials used in part marking and identification. The experiment contained Data Matrix symbols applied using laser bonding, vacuum arc vapor deposition, gas assisted laser etch, chemical etch, mechanical dot peening, laser shot peening, and laser induced surface improvement. The effects of ultraviolet radiation on nickel acetate seal versus hot water seal on sulfuric acid anodized aluminum are discussed. These samples were exposed on the International Space Station to the low Earth orbital environment of atomic oxygen, ultraviolet radiation, thermal cycling, and hard vacuum, though atomic oxygen exposure was very limited for some samples. Results from the one-year exposure on MISSE-3 and MISSE-4 are compared to those from MISSE-1 and MISSE-2, which were exposed for four years. Part marking and identification materials on the current MISSE -6 experiment are also discussed.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pichara, Karim; Protopapas, Pavlos

We present an automatic classification method for astronomical catalogs with missing data. We use Bayesian networks and a probabilistic graphical model that allows us to perform inference to predict missing values given observed data and dependency relationships between variables. To learn a Bayesian network from incomplete data, we use an iterative algorithm that utilizes sampling methods and expectation maximization to estimate the distributions and probabilistic dependencies of variables from data with missing values. To test our model, we use three catalogs with missing data (SAGE, Two Micron All Sky Survey, and UBVI) and one complete catalog (MACHO). We examine howmore » classification accuracy changes when information from missing data catalogs is included, how our method compares to traditional missing data approaches, and at what computational cost. Integrating these catalogs with missing data, we find that classification of variable objects improves by a few percent and by 15% for quasar detection while keeping the computational cost the same.« less

The Strengths and Limitations of South Africa’s Search for Apartheid-Era Missing Persons

PubMed Central

Aronson, Jay D.

2011-01-01

This article examines efforts to account for missing persons from the apartheid era in South Africa by family members, civil society organizations and the current government’s Missing Persons Task Team, which emerged out of the Truth and Reconciliation Commission process. It focuses on how missing persons have been officially defined in the South African context and the extent to which the South African government is able to address the current needs and desires of relatives of the missing. I make two main arguments: that family members ought to have an active role in shaping the initiatives and institutions that seek to resolve the fate of missing people, and that the South African government ought to take a more holistic ‘grave-to-grave’ approach to the process of identifying, returning and reburying the remains of the missing. PMID:21984885

Missing: Children and Young People with SEBD

ERIC Educational Resources Information Center

Visser, John; Daniels, Harry; Macnab, Natasha

2005-01-01

This article explores the issue of missing from and missing out on education. It argues that too little is known with regard to the characteristics of children and young people missing from schooling. It postulates that many of these pupils will have social, emotional and behavioural difficulties which are largely unrecognized and thus not…

40 CFR 98.416 - Data reporting requirements.

Code of Federal Regulations, 2010 CFR

2010-07-01

.... (16) Where missing data have been estimated pursuant to § 98.415, the reason the data were missing, the length of time the data were missing, the method used to estimate the missing data, and the... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Data reporting requirements. 98.416...

40 CFR 98.285 - Procedures for estimating missing data.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Procedures for estimating missing data... estimating missing data. For the petroleum coke input procedure in § 98.283(b), a complete record of all...) For each missing value of the monthly carbon content of petroleum coke, the substitute data value...

40 CFR 98.95 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... estimating missing data. (a) Except as provided in paragraph (b) of this section, a complete record of all... required. (b) If you use fluorinated heat transfer fluids at your facility and are missing data for one or...

40 CFR 75.33 - Standard missing data procedures for SO2, NOX, Hg, and flow rate.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 16 2010-07-01 2010-07-01 false Standard missing data procedures for... AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.33 Standard missing data procedures for SO2, NOX, Hg, and flow rate. (a) Following initial...

40 CFR 98.205 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... estimating missing data. (a) A complete record of all measured parameters used in the GHG emission... substitute data value for the missing parameter will be used in the calculations as specified in paragraph (b...

40 CFR 98.255 - Procedures for estimating missing data.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... during unit operation or if a required fuel sample is not taken), a substitute data value for the missing...

40 CFR 98.415 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... Procedures for estimating missing data. (a) A complete record of all measured parameters used in the GHG... unavailable (e.g., if a meter malfunctions), a substitute data value for the missing parameter shall be used...

40 CFR 75.33 - Standard missing data procedures for SO2, NOX, and flow rate.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 16 2011-07-01 2011-07-01 false Standard missing data procedures for... (CONTINUED) AIR PROGRAMS (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.33 Standard missing data procedures for SO2, NOX, and flow rate. (a) Following initial certification...

40 CFR 98.315 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... estimating missing data. For the petroleum coke input procedure in § 98.313(b), a complete record of all... substitute data value for the missing parameter shall be used in the calculations as specified in the...

40 CFR 98.85 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... missing data. A complete record of all measured parameters used in the GHG emissions calculations in § 98... substitute data value for the missing parameter shall be used in the calculations. The owner or operator must...

40 CFR 98.425 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... estimating missing data. (a) Whenever the quality assurance procedures in § 98.424(a)(1) of this subpart... following missing data procedures shall be followed: (1) A quarterly CO2 mass flow or volumetric flow value...

Missing Data and Institutional Research

ERIC Educational Resources Information Center

Croninger, Robert G.; Douglas, Karen M.

2005-01-01

Many do not consider the effect that missing data have on their survey results nor do they know how to handle missing data. This chapter offers strategies for handling item-missing data and provides a practical example of how these strategies may affect results. The chapter concludes with recommendations for preventing and dealing with missing…

40 CFR 98.235 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... Procedures for estimating missing data. A complete record of all estimated and/or measured parameters used in... sources as soon as possible, including in the subsequent calendar year if missing data are not discovered...

40 CFR 98.85 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... missing data. A complete record of all measured parameters used in the GHG emissions calculations in § 98... substitute data value for the missing parameter shall be used in the calculations. The owner or operator must...

40 CFR 98.415 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... Procedures for estimating missing data. (a) A complete record of all measured parameters used in the GHG... unavailable (e.g., if a meter malfunctions), a substitute data value for the missing parameter shall be used...

40 CFR 98.295 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... estimating missing data. For the emission calculation methodologies in § 98.293(b)(2) and (b)(3), a complete... unavailable, a substitute data value for the missing parameter shall be used in the calculations as specified...

40 CFR 98.285 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... estimating missing data. For the petroleum coke input procedure in § 98.283(b), a complete record of all...) For each missing value of the monthly carbon content of petroleum coke, the substitute data value...

40 CFR 98.95 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... estimating missing data. (a) Except as provided in paragraph (b) of this section, a complete record of all... required. (b) If you use fluorinated heat transfer fluids at your facility and are missing data for one or...

40 CFR 98.85 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... missing data. A complete record of all measured parameters used in the GHG emissions calculations in § 98... substitute data value for the missing parameter shall be used in the calculations. The owner or operator must...

40 CFR Appendix C to Part 75 - Missing Data Estimation Procedures

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 17 2013-07-01 2013-07-01 false Missing Data Estimation Procedures C... (CONTINUED) CONTINUOUS EMISSION MONITORING Pt. 75, App. C Appendix C to Part 75—Missing Data Estimation Procedures 1. Parametric Monitoring Procedure for Missing SO2 Concentration or NOX Emission Rate Data 1...

40 CFR 98.185 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... missing data. A complete record of all measured parameters used in the GHG emissions calculations in § 98... substitute data value for the missing parameter shall be used in the calculations as specified in the...

40 CFR 98.85 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... missing data. A complete record of all measured parameters used in the GHG emissions calculations in § 98... substitute data value for the missing parameter shall be used in the calculations. The owner or operator must...

40 CFR 98.425 - Procedures for estimating missing data.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Procedures for estimating missing data... estimating missing data. (a) Whenever the quality assurance procedures in § 98.424(a) of this subpart cannot... following missing data procedures shall be followed: (1) A quarterly CO2 mass flow or volumetric flow value...

40 CFR 98.235 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... Procedures for estimating missing data. A complete record of all estimated and/or measured parameters used in... sources as soon as possible, including in the subsequent calendar year if missing data are not discovered...

40 CFR Appendix C to Part 75 - Missing Data Estimation Procedures

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 17 2014-07-01 2014-07-01 false Missing Data Estimation Procedures C... (CONTINUED) CONTINUOUS EMISSION MONITORING Pt. 75, App. C Appendix C to Part 75—Missing Data Estimation Procedures 1. Parametric Monitoring Procedure for Missing SO2 Concentration or NOX Emission Rate Data 1...

40 CFR 98.205 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... estimating missing data. (a) A complete record of all measured parameters used in the GHG emission... substitute data value for the missing parameter will be used in the calculations as specified in paragraph (b...

40 CFR 98.255 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... during unit operation or if a required fuel sample is not taken), a substitute data value for the missing...

40 CFR 98.205 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... estimating missing data. (a) A complete record of all measured parameters used in the GHG emission... substitute data value for the missing parameter will be used in the calculations as specified in paragraph (b...

40 CFR 98.285 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... estimating missing data. For the petroleum coke input procedure in § 98.283(b), a complete record of all...) For each missing value of the monthly carbon content of petroleum coke, the substitute data value...

40 CFR 98.185 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... missing data. A complete record of all measured parameters used in the GHG emissions calculations in § 98... substitute data value for the missing parameter shall be used in the calculations as specified in the...

40 CFR 98.255 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... during unit operation or if a required fuel sample is not taken), a substitute data value for the missing...

40 CFR 98.315 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... estimating missing data. For the petroleum coke input procedure in § 98.313(b), a complete record of all... substitute data value for the missing parameter shall be used in the calculations as specified in the...

40 CFR 98.315 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... estimating missing data. For the petroleum coke input procedure in § 98.313(b), a complete record of all... substitute data value for the missing parameter shall be used in the calculations as specified in the...

40 CFR Appendix C to Part 75 - Missing Data Estimation Procedures

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 17 2012-07-01 2012-07-01 false Missing Data Estimation Procedures C... (CONTINUED) CONTINUOUS EMISSION MONITORING Pt. 75, App. C Appendix C to Part 75—Missing Data Estimation Procedures 1. Parametric Monitoring Procedure for Missing SO2 Concentration or NOX Emission Rate Data 1...

40 CFR 98.205 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... estimating missing data. (a) A complete record of all measured parameters used in the GHG emission... substitute data value for the missing parameter will be used in the calculations as specified in paragraph (b...

40 CFR 98.235 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... Procedures for estimating missing data. A complete record of all estimated and/or measured parameters used in... sources as soon as possible, including in the subsequent calendar year if missing data are not discovered...

40 CFR 98.315 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... estimating missing data. For the petroleum coke input procedure in § 98.313(b), a complete record of all... substitute data value for the missing parameter shall be used in the calculations as specified in the...

40 CFR 98.295 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... estimating missing data. For the emission calculation methodologies in § 98.293(b)(2) and (b)(3), a complete... unavailable, a substitute data value for the missing parameter shall be used in the calculations as specified...

40 CFR 98.95 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... estimating missing data. (a) Except as provided in paragraph (b) of this section, a complete record of all... required. (b) If you use fluorinated heat transfer fluids at your facility and are missing data for one or...

40 CFR 75.33 - Standard missing data procedures for SO2, NOX, and flow rate.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 17 2012-07-01 2012-07-01 false Standard missing data procedures for... (CONTINUED) AIR PROGRAMS (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.33 Standard missing data procedures for SO2, NOX, and flow rate. (a) Following initial certification...

40 CFR 98.425 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... estimating missing data. (a) Whenever the quality assurance procedures in § 98.424(a)(1) of this subpart... following missing data procedures shall be followed: (1) A quarterly CO2 mass flow or volumetric flow value...

40 CFR 98.185 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... missing data. A complete record of all measured parameters used in the GHG emissions calculations in § 98... substitute data value for the missing parameter shall be used in the calculations as specified in the...

40 CFR 98.285 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... estimating missing data. For the petroleum coke input procedure in § 98.283(b), a complete record of all...) For each missing value of the monthly carbon content of petroleum coke, the substitute data value...

40 CFR 98.285 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... estimating missing data. For the petroleum coke input procedure in § 98.283(b), a complete record of all...) For each missing value of the monthly carbon content of petroleum coke, the substitute data value...

40 CFR 75.33 - Standard missing data procedures for SO2, NOX, and flow rate.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 17 2013-07-01 2013-07-01 false Standard missing data procedures for... (CONTINUED) AIR PROGRAMS (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.33 Standard missing data procedures for SO2, NOX, and flow rate. (a) Following initial certification...

A Probability Based Framework for Testing the Missing Data Mechanism

ERIC Educational Resources Information Center

Lin, Johnny Cheng-Han

2013-01-01

Many methods exist for imputing missing data but fewer methods have been proposed to test the missing data mechanism. Little (1988) introduced a multivariate chi-square test for the missing completely at random data mechanism (MCAR) that compares observed means for each pattern with expectation-maximization (EM) estimated means. As an alternative,…

40 CFR 98.255 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... during unit operation or if a required fuel sample is not taken), a substitute data value for the missing...

40 CFR 98.195 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... estimating missing data. For the procedure in § 98.193(b)(1), a complete record of all measured parameters... all available process data or data used for accounting purposes. (b) For missing values related to the...

40 CFR 98.235 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... Procedures for estimating missing data. A complete record of all estimated and/or measured parameters used in... sources as soon as possible, including in the subsequent calendar year if missing data are not discovered...

40 CFR 98.295 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... estimating missing data. For the emission calculation methodologies in § 98.293(b)(2) and (b)(3), a complete... unavailable, a substitute data value for the missing parameter shall be used in the calculations as specified...

40 CFR 98.415 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... Procedures for estimating missing data. (a) A complete record of all measured parameters used in the GHG... unavailable (e.g., if a meter malfunctions), a substitute data value for the missing parameter shall be used...

40 CFR 98.415 - Procedures for estimating missing data.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Procedures for estimating missing data... Procedures for estimating missing data. (a) A complete record of all measured parameters used in the GHG... unavailable (e.g., if a meter malfunctions), a substitute data value for the missing parameter shall be used...

40 CFR 98.185 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... missing data. A complete record of all measured parameters used in the GHG emissions calculations in § 98... substitute data value for the missing parameter shall be used in the calculations as specified in the...

Comparison of Two Approaches for Handling Missing Covariates in Logistic Regression

ERIC Educational Resources Information Center

Peng, Chao-Ying Joanne; Zhu, Jin

2008-01-01

For the past 25 years, methodological advances have been made in missing data treatment. Most published work has focused on missing data in dependent variables under various conditions. The present study seeks to fill the void by comparing two approaches for handling missing data in categorical covariates in logistic regression: the…

Best Practices for Missing Data Management in Counseling Psychology

ERIC Educational Resources Information Center

Schlomer, Gabriel L.; Bauman, Sheri; Card, Noel A.

2010-01-01

This article urges counseling psychology researchers to recognize and report how missing data are handled, because consumers of research cannot accurately interpret findings without knowing the amount and pattern of missing data or the strategies that were used to handle those data. Patterns of missing data are reviewed, and some of the common…

40 CFR 98.425 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... estimating missing data. (a) Whenever the quality assurance procedures in § 98.424(a)(1) of this subpart... following missing data procedures shall be followed: (1) A quarterly CO2 mass flow or volumetric flow value...

40 CFR 98.295 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... estimating missing data. For the emission calculation methodologies in § 98.293(b)(2) and (b)(3), a complete... unavailable, a substitute data value for the missing parameter shall be used in the calculations as specified...

40 CFR 98.255 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations... during unit operation or if a required fuel sample is not taken), a substitute data value for the missing...

40 CFR 98.425 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... estimating missing data. (a) Whenever the quality assurance procedures in § 98.424(a)(1) of this subpart... following missing data procedures shall be followed: (1) A quarterly CO2 mass flow or volumetric flow value...

40 CFR 98.415 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... Procedures for estimating missing data. (a) A complete record of all measured parameters used in the GHG... unavailable (e.g., if a meter malfunctions), a substitute data value for the missing parameter shall be used...

40 CFR Appendix C to Part 75 - Missing Data Estimation Procedures

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 16 2011-07-01 2011-07-01 false Missing Data Estimation Procedures C... (CONTINUED) CONTINUOUS EMISSION MONITORING Pt. 75, App. C Appendix C to Part 75—Missing Data Estimation Procedures 1. Parametric Monitoring Procedure for Missing SO2 Concentration or NOX Emission Rate Data 1...

40 CFR 75.33 - Standard missing data procedures for SO2, NOX, and flow rate.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 17 2014-07-01 2014-07-01 false Standard missing data procedures for... (CONTINUED) AIR PROGRAMS (CONTINUED) CONTINUOUS EMISSION MONITORING Missing Data Substitution Procedures § 75.33 Standard missing data procedures for SO2, NOX, and flow rate. (a) Following initial certification...

On Testability of Missing Data Mechanisms in Incomplete Data Sets

ERIC Educational Resources Information Center

Raykov, Tenko

2011-01-01

This article is concerned with the question of whether the missing data mechanism routinely referred to as missing completely at random (MCAR) is statistically examinable via a test for lack of distributional differences between groups with observed and missing data, and related consequences. A discussion is initially provided, from a formal logic…

Silver Alerts and the Problem of Missing Adults with Dementia

ERIC Educational Resources Information Center

Carr, Dawn; Muschert, Glenn W.; Kinney, Jennifer; Robbins, Emily; Petonito, Gina; Manning, Lydia; Brown, J. Scott

2010-01-01

In the months following the introduction of the National AMBER (America's Missing: Broadcast Emergency Response) Alert plan used to locate missing and abducted children, Silver Alert programs began to emerge. These programs use the same infrastructure and approach to find a different missing population, cognitively impaired older adults. By late…

Capture Their Attention: Capturing Lessons Using Screen Capture Software

ERIC Educational Resources Information Center

Drumheller, Kristina; Lawler, Gregg

2011-01-01

When students miss classes for university activities such as athletic and academic events, they inevitably miss important class material. Students can get notes from their peers or visit professors to find out what they missed, but when students miss new and challenging material these steps are sometimes not enough. Screen capture and recording…

The MISSE-9 Polymers and Composites Experiment Being Flown on the MISSE-Flight Facility

NASA Technical Reports Server (NTRS)

De Groh, Kim K.; Banks, Bruce A.

2017-01-01

Materials on the exterior of spacecraft in low Earth orbit (LEO) are subject to extremely harsh environmental conditions, including various forms of radiation (cosmic rays, ultraviolet, x-ray, and charged particle radiation), micrometeoroids and orbital debris, temperature extremes, thermal cycling, and atomic oxygen (AO). These environmental exposures can result in erosion, embrittlement and optical property degradation of susceptible materials, threatening spacecraft performance and durability. To increase our understanding of space environmental effects such as AO erosion and radiation induced embrittlement of spacecraft materials, NASA Glenn has developed a series of experiments flown as part of the Materials International Space Station Experiment (MISSE) missions on the exterior of the International Space Station (ISS). These experiments have provided critical LEO space environment durability data such as AO erosion yield values for many materials and mechanical properties changes after long term space exposure. In continuing these studies, a new Glenn experiment has been proposed, and accepted, for flight on the new MISSE-Flight Facility (MISSE-FF). This experiment is called the Polymers and Composites Experiment and it will be flown as part of the MISSE-9 mission, the inaugural mission of MISSE-FF. Figure 1 provides an artist rendition of MISSE-FF ISS external platform. The MISSE-FF is manifested for launch on SpaceX-13.

Standards should be applied in the prevention and handling of missing data for patient-centered outcomes research: a systematic review and expert consensus.

PubMed

Li, Tianjing; Hutfless, Susan; Scharfstein, Daniel O; Daniels, Michael J; Hogan, Joseph W; Little, Roderick J A; Roy, Jason A; Law, Andrew H; Dickersin, Kay

2014-01-01

To recommend methodological standards in the prevention and handling of missing data for primary patient-centered outcomes research (PCOR). We searched National Library of Medicine Bookshelf and Catalog as well as regulatory agencies' and organizations' Web sites in January 2012 for guidance documents that had formal recommendations regarding missing data. We extracted the characteristics of included guidance documents and recommendations. Using a two-round modified Delphi survey, a multidisciplinary panel proposed mandatory standards on the prevention and handling of missing data for PCOR. We identified 1,790 records and assessed 30 as having relevant recommendations. We proposed 10 standards as mandatory, covering three domains. First, the single best approach is to prospectively prevent missing data occurrence. Second, use of valid statistical methods that properly reflect multiple sources of uncertainty is critical when analyzing missing data. Third, transparent and thorough reporting of missing data allows readers to judge the validity of the findings. We urge researchers to adopt rigorous methodology and promote good science by applying best practices to the prevention and handling of missing data. Developing guidance on the prevention and handling of missing data for observational studies and studies that use existing records is a priority for future research. Copyright © 2014 Elsevier Inc. All rights reserved.

Identifying Heat Waves in Florida: Considerations of Missing Weather Data

PubMed Central

Leary, Emily; Young, Linda J.; DuClos, Chris; Jordan, Melissa M.

2015-01-01

Background Using current climate models, regional-scale changes for Florida over the next 100 years are predicted to include warming over terrestrial areas and very likely increases in the number of high temperature extremes. No uniform definition of a heat wave exists. Most past research on heat waves has focused on evaluating the aftermath of known heat waves, with minimal consideration of missing exposure information. Objectives To identify and discuss methods of handling and imputing missing weather data and how those methods can affect identified periods of extreme heat in Florida. Methods In addition to ignoring missing data, temporal, spatial, and spatio-temporal models are described and utilized to impute missing historical weather data from 1973 to 2012 from 43 Florida weather monitors. Calculated thresholds are used to define periods of extreme heat across Florida. Results Modeling of missing data and imputing missing values can affect the identified periods of extreme heat, through the missing data itself or through the computed thresholds. The differences observed are related to the amount of missingness during June, July, and August, the warmest months of the warm season (April through September). Conclusions Missing data considerations are important when defining periods of extreme heat. Spatio-temporal methods are recommended for data imputation. A heat wave definition that incorporates information from all monitors is advised. PMID:26619198

Identifying Heat Waves in Florida: Considerations of Missing Weather Data.

PubMed

Leary, Emily; Young, Linda J; DuClos, Chris; Jordan, Melissa M

2015-01-01

Using current climate models, regional-scale changes for Florida over the next 100 years are predicted to include warming over terrestrial areas and very likely increases in the number of high temperature extremes. No uniform definition of a heat wave exists. Most past research on heat waves has focused on evaluating the aftermath of known heat waves, with minimal consideration of missing exposure information. To identify and discuss methods of handling and imputing missing weather data and how those methods can affect identified periods of extreme heat in Florida. In addition to ignoring missing data, temporal, spatial, and spatio-temporal models are described and utilized to impute missing historical weather data from 1973 to 2012 from 43 Florida weather monitors. Calculated thresholds are used to define periods of extreme heat across Florida. Modeling of missing data and imputing missing values can affect the identified periods of extreme heat, through the missing data itself or through the computed thresholds. The differences observed are related to the amount of missingness during June, July, and August, the warmest months of the warm season (April through September). Missing data considerations are important when defining periods of extreme heat. Spatio-temporal methods are recommended for data imputation. A heat wave definition that incorporates information from all monitors is advised.

A study of using smartphone to detect and identify construction workers' near-miss falls based on ANN

NASA Astrophysics Data System (ADS)

Zhang, Mingyuan; Cao, Tianzhuo; Zhao, Xuefeng

2018-03-01

As an effective fall accident preventive method, insight into near-miss falls provides an efficient solution to find out the causes of fall accidents, classify the type of near-miss falls and control the potential hazards. In this context, the paper proposes a method to detect and identify near-miss falls that occur when a worker walks in a workplace based on artificial neural network (ANN). The energy variation generated by workers who meet with near-miss falls is measured by sensors embedded in smart phone. Two experiments were designed to train the algorithm to identify various types of near-miss falls and test the recognition accuracy, respectively. At last, a test was conducted by workers wearing smart phones as they walked around a simulated construction workplace. The motion data was collected, processed and inputted to the trained ANN to detect and identify near-miss falls. Thresholds were obtained to measure the relationship between near-miss falls and fall accidents in a quantitate way. This approach, which integrates smart phone and ANN, will help detect near-miss fall events, identify hazardous elements and vulnerable workers, providing opportunities to eliminate dangerous conditions in a construction site or to alert possible victims that need to change their behavior before the occurrence of a fall accident.

Depression and literacy are important factors for missed appointments.

PubMed

Miller-Matero, Lisa Renee; Clark, Kalin Burkhardt; Brescacin, Carly; Dubaybo, Hala; Willens, David E

2016-09-01

Multiple variables are related to missed clinic appointments. However, the prevalence of missed appointments is still high suggesting other factors may play a role. The purpose of this study was to investigate the relationship between missed appointments and multiple variables simultaneously across a health care system, including patient demographics, psychiatric symptoms, cognitive functioning and literacy status. Chart reviews were conducted on 147 consecutive patients who were seen by a primary care psychologist over a six month period and completed measures to determine levels of depression, anxiety, sleep, cognitive functioning and health literacy. Demographic information and rates of missed appointments were also collected from charts. The average rate of missed appointments was 15.38%. In univariate analyses, factors related to higher rates of missed appointments included younger age (p = .03), lower income (p = .05), probable depression (p = .05), sleep difficulty (p = .05) and limited reading ability (p = .003). There were trends for a higher rate of missed appointments for patients identifying as black (p = .06), government insurance (p = .06) and limited math ability (p = .06). In a multivariate model, probable depression (p = .02) and limited reading ability (p = .003) were the only independent predictors. Depression and literacy status may be the most important factors associated with missed appointments. Implications are discussed including regular screening for depression and literacy status as well as interventions that can be utilized to help improve the rate of missed appointments.

Protannotator: a semiautomated pipeline for chromosome-wise functional annotation of the "missing" human proteome.

PubMed

Islam, Mohammad T; Garg, Gagan; Hancock, William S; Risk, Brian A; Baker, Mark S; Ranganathan, Shoba

2014-01-03

The chromosome-centric human proteome project (C-HPP) aims to define the complete set of proteins encoded in each human chromosome. The neXtProt database (September 2013) lists 20,128 proteins for the human proteome, of which 3831 human proteins (∼19%) are considered "missing" according to the standard metrics table (released September 27, 2013). In support of the C-HPP initiative, we have extended the annotation strategy developed for human chromosome 7 "missing" proteins into a semiautomated pipeline to functionally annotate the "missing" human proteome. This pipeline integrates a suite of bioinformatics analysis and annotation software tools to identify homologues and map putative functional signatures, gene ontology, and biochemical pathways. From sequential BLAST searches, we have primarily identified homologues from reviewed nonhuman mammalian proteins with protein evidence for 1271 (33.2%) "missing" proteins, followed by 703 (18.4%) homologues from reviewed nonhuman mammalian proteins and subsequently 564 (14.7%) homologues from reviewed human proteins. Functional annotations for 1945 (50.8%) "missing" proteins were also determined. To accelerate the identification of "missing" proteins from proteomics studies, we generated proteotypic peptides in silico. Matching these proteotypic peptides to ENCODE proteogenomic data resulted in proteomic evidence for 107 (2.8%) of the 3831 "missing proteins, while evidence from a recent membrane proteomic study supported the existence for another 15 "missing" proteins. The chromosome-wise functional annotation of all "missing" proteins is freely available to the scientific community through our web server (http://biolinfo.org/protannotator).

Learning from near misses: from quick fixes to closing off the Swiss-cheese holes.

PubMed

Jeffs, Lianne; Berta, Whitney; Lingard, Lorelei; Baker, G Ross

2012-04-01

The extent to which individuals in healthcare use near misses as learning opportunities remains poorly understood. Thus, an exploratory study was conducted to gain insight into the nature of, and contributing factors to, organisational learning from near misses in clinical practice. A constructivist grounded theory approach was employed which included semi-structured interviews with 24 participants (16 clinicians and 8 administrators) from a large teaching hospital in Canada. This study revealed three scenarios for the responses to near misses, the most common involved 'doing a quick fix' where clinicians recognised and corrected an error with no further action. The second scenario consisted of reporting near misses but not hearing back from management, which some participants characterised as 'going into a black hole'. The third scenario was 'closing off the Swiss-cheese holes', in which a reported near miss generated corrective action at an organisational level. Explanations for 'doing a quick fix' included the pervasiveness of near misses that cause no harm and fear associated with reporting the near miss. 'Going into a black hole' reflected managers' focus on operational duties and events that harmed patients. 'Closing off the Swiss-cheese holes' occurred when managers perceived substantial potential for harm and preventability. Where learning was perceived to occur, leaders played a pivotal role in encouraging near-miss reporting. To optimise learning, organisations will need to determine which near misses are appropriate to be responded to as 'quick fixes' and which ones require further action at the unit and corporate levels.

Depression, Anxiety and Somatization in Women with War Missing Family Members

PubMed Central

Baraković, Devla; Avdibegović, Esmina; Sinanović, Osman

2013-01-01

Introduction: During the war circumstances, women and children are exposed to multiple traumatic experiences, one of which is an violent disappearance of a family member. Goal: The aim of this research was to establish the presence of symptoms of depression, anxiety and somatization in women in Bosnia and Herzegovina who have sought their war missing family members for 15 to 18 years. Subjects and Methods: The research was based on a sample of 120 women with war missing family member and 40 women without a war missing family member as a control group. For assessment of depression, anxiety and symptoms of somatization the self-rating Beck Depression Inventory (BDI), Hamilton Anxiety Rating Scale (HAM-A), Somatic Symptoms Index (SSI) questionnaire and a general questionnaire on the sociodemographic data and data on war missing family members were used. Results: A significantly higher intensity of symptoms of depression (p<0.001), anxiety (p<0.001) and somatization (p = 0.013) was present in women with, in comparison to women without a missing family member. In comparison of the kinship with the missing family members, statistically significantly higher intensity of symptoms of depression, anxiety and somatization was in women with a missing child (p<0.001) in comparison to other missing family members. Conclusion: A prolonged period of seeking, waiting and uncertainty of what happened in the war with the missing family member presents for those women a prolonged suffering manifested through depression, anxiety and symptoms of somatization. PMID:24167436

Should genes with missing data be excluded from phylogenetic analyses?

PubMed

Jiang, Wei; Chen, Si-Yun; Wang, Hong; Li, De-Zhu; Wiens, John J

2014-11-01

Phylogeneticists often design their studies to maximize the number of genes included but minimize the overall amount of missing data. However, few studies have addressed the costs and benefits of adding characters with missing data, especially for likelihood analyses of multiple loci. In this paper, we address this topic using two empirical data sets (in yeast and plants) with well-resolved phylogenies. We introduce varying amounts of missing data into varying numbers of genes and test whether the benefits of excluding genes with missing data outweigh the costs of excluding the non-missing data that are associated with them. We also test if there is a proportion of missing data in the incomplete genes at which they cease to be beneficial or harmful, and whether missing data consistently bias branch length estimates. Our results indicate that adding incomplete genes generally increases the accuracy of phylogenetic analyses relative to excluding them, especially when there is a high proportion of incomplete genes in the overall dataset (and thus few complete genes). Detailed analyses suggest that adding incomplete genes is especially helpful for resolving poorly supported nodes. Given that we find that excluding genes with missing data often decreases accuracy relative to including these genes (and that decreases are generally of greater magnitude than increases), there is little basis for assuming that excluding these genes is necessarily the safer or more conservative approach. We also find no evidence that missing data consistently bias branch length estimates. Copyright © 2014 Elsevier Inc. All rights reserved.

What impact do assumptions about missing data have on conclusions? A practical sensitivity analysis for a cancer survival registry.

PubMed

Smuk, M; Carpenter, J R; Morris, T P

2017-02-06

Within epidemiological and clinical research, missing data are a common issue and often over looked in publications. When the issue of missing observations is addressed it is usually assumed that the missing data are 'missing at random' (MAR). This assumption should be checked for plausibility, however it is untestable, thus inferences should be assessed for robustness to departures from missing at random. We highlight the method of pattern mixture sensitivity analysis after multiple imputation using colorectal cancer data as an example. We focus on the Dukes' stage variable which has the highest proportion of missing observations. First, we find the probability of being in each Dukes' stage given the MAR imputed dataset. We use these probabilities in a questionnaire to elicit prior beliefs from experts on what they believe the probability would be in the missing data. The questionnaire responses are then used in a Dirichlet draw to create a Bayesian 'missing not at random' (MNAR) prior to impute the missing observations. The model of interest is applied and inferences are compared to those from the MAR imputed data. The inferences were largely insensitive to departure from MAR. Inferences under MNAR suggested a smaller association between Dukes' stage and death, though the association remained positive and with similarly low p values. We conclude by discussing the positives and negatives of our method and highlight the importance of making people aware of the need to test the MAR assumption.

Missed rib fractures on evaluation of initial chest CT for trauma patients: pattern analysis and diagnostic value of coronal multiplanar reconstruction images with multidetector row CT.

PubMed

Cho, S H; Sung, Y M; Kim, M S

2012-10-01

The objective of this study was to review the prevalence and radiological features of rib fractures missed on initial chest CT evaluation, and to examine the diagnostic value of additional coronal images in a large series of trauma patients. 130 patients who presented to an emergency room for blunt chest trauma underwent multidetector row CT of the thorax within the first hour during their stay, and had follow-up CT or bone scans as diagnostic gold standards. Images were evaluated on two separate occasions: once with axial images and once with both axial and coronal images. The detection rates of missed rib fractures were compared between readings using a non-parametric method of clustered data. In the cases of missed rib fractures, the shapes, locations and associated fractures were evaluated. 58 rib fractures were missed with axial images only and 52 were missed with both axial and coronal images (p=0.088). The most common shape of missed rib fractures was buckled (56.9%), and the anterior arc (55.2%) was most commonly involved. 21 (36.2%) missed rib fractures had combined fractures on the same ribs, and 38 (65.5%) were accompanied by fracture on neighbouring ribs. Missed rib fractures are not uncommon, and radiologists should be familiar with buckle fractures, which are frequently missed. Additional coronal imagescan be helpful in the diagnosis of rib fractures that are not seen on axial images.

Predictors of missed appointments in patients referred for congenital or pediatric cardiac magnetic resonance.

PubMed

Lu, Jimmy C; Lowery, Ray; Yu, Sunkyung; Ghadimi Mahani, Maryam; Agarwal, Prachi P; Dorfman, Adam L

2017-07-01

Congenital cardiac magnetic resonance is a limited resource because of scanner and physician availability. Missed appointments decrease scheduling efficiency, have financial implications and represent missed care opportunities. To characterize the rate of missed appointments and identify modifiable predictors. This single-center retrospective study included all patients with outpatient congenital or pediatric cardiac MR appointments from Jan. 1, 2014, through Dec. 31, 2015. We identified missed appointments (no-shows or same-day cancellations) from the electronic medical record. We obtained demographic and clinical factors from the medical record and assessed socioeconomic factors by U.S. Census block data by patient ZIP code. Statistically significant variables (P<0.05) were included into a multivariable analysis. Of 795 outpatients (median age 18.5 years, interquartile range 13.4-27.1 years) referred for congenital cardiac MR, a total of 91 patients (11.4%) missed appointments; 28 (3.5%) missed multiple appointments. Reason for missed appointment could be identified in only 38 patients (42%), but of these, 28 (74%) were preventable or could have been identified prior to the appointment. In multivariable analysis, independent predictors of missed appointments were referral by a non-cardiologist (adjusted odds ratio [AOR] 5.8, P=0.0002), referral for research (AOR 3.6, P=0.01), having public insurance (AOR 2.1, P=0.004), and having scheduled cardiac MR from November to April (AOR 1.8, P=0.01). Demographic factors can identify patients at higher risk for missing appointments. These data may inform initiatives to limit missed appointments, such as targeted education of referring providers and patients. Further data are needed to evaluate the efficacy of potential interventions.

[Near miss outcomes in gambling games].

PubMed

Pecsenye, Zsuzsa; Kurucz, Gyozo

2017-01-01

Games of chance operate with an intermittent reinforcement schedule in which the number of games takes the player to win differ in each turn thus they can not predict when the next positive reinforcement arrives. The near miss outcome (close to winning but actually a losing outcome) can be interpreted as a secondary (built in) reinforcement within variable ratio reinforcement schedule that presumably contribute to the development and maintanance of gambling addiction. The aim of this publication would be to introduce near miss outcomes and to summarize and critically analyze literature connected to this issue.We searched internet datebases using word "near miss" and analyse articles focusing on gambling games. Based on numerous authors' results a near miss rate set at around 30% increases the desire to continue playing among gamblers and players who have no former gambling experience as well. Some studies have demonstrated that this effect might be related to the extent the player has the situation under control during the gambling session. The hypothetical inhibiting effect of a 45% near miss ratio has not yet been proven. Neurobiological researches show middle-cerebral activity during near miss outcomes furthermore similar physiological patterns have been discovered following a near miss and winning outcomes. Regarding the connection between intrapsychic variables (cognitive and personality factors) and near misses there are very few studies. The fact that different authors interpret near miss outcomes differently even when studying the same game leads to problems in interpreting their results. It follows from the foregoing empirical results that near miss outcomes contribute to the development and maintanance of pathological gambling but we have little information on the factors implementing this effect.

Predictors of the frequency and subjective experience of cycling near misses: Findings from the first two years of the UK Near Miss Project.

PubMed

Aldred, Rachel; Goodman, Anna

2018-01-01

Using 2014 and 2015 data from the UK Near Miss Project, this paper examines the stability of self-report incident rates for cycling near misses across these two years. It further examines the stability of the individual-level predictors of experiencing a near miss, including what influences the scariness of an incident. The paper uses three questions asked for only in 2015, which allow further exploration of factors shaping near miss rates and impacts of incidents. Firstly, a respondent's level of cycling experience; secondly, whether an incident was perceived as deliberate; and finally, whether the respondent themselves described the incident as a 'near miss' (as opposed to only a frightening and/or annoying non-injury incident). Using this data, we find a decline of almost a third in incident rates in 2015 compared to 2014, which we believe is likely to be largely an artefact due to differences in reporting rates. This suggests caution about interpreting small fluctuations in subjectively reported near miss rates. However, in both years near miss rates are many times more frequent than injury collisions. In both years of data collection our findings are very similar in terms of the patterning of incident types, and how frightening different incident categories are, which increases confidence in these findings. We find that new cyclists experience very high incident rates compared to other cyclists, and test a conceptual model explaining how perceived deliberateness, near-miss status, and scariness are connected. For example, incidents that are perceived to be deliberate are more likely to be experienced as very frightening, independent of their 'near miss' status. Copyright © 2017 Elsevier Ltd. All rights reserved.

Parentage determination of Vanda Miss Joaquim (Orchidaceae) through two chloroplast genes rbcL and matK

PubMed Central

Khew, Gillian Su-Wen; Chia, Tet Fatt

2011-01-01

Background and aims The popular hybrid orchid Vanda Miss Joaquim was made Singapore's national flower in 1981. It was originally described in the Gardeners’ Chronicle in 1893, as a cross between Vanda hookeriana and Vanda teres. However, no record had been kept as to which parent contributed the pollen. This study was conducted using DNA barcoding techniques to determine the pod parent of V. Miss Joaquim, thereby inferring the pollen parent of the hybrid by exclusion. Methodology Two chloroplast genes, matK and rbcL, from five related taxa, V. hookeriana, V. teres var. alba, V. teres var. andersonii, V. teres var. aurorea and V. Miss Joaquim ‘Agnes’, were sequenced. The matK gene from herbarium specimens of V. teres and V. Miss Joaquim, both collected in 1893, was also sequenced. Principal results No sequence variation was found in the 600-bp region of rbcL sequenced. Sequence variation was found in the matK gene of V. hookeriana, V. teres var. alba, V. teres var. aurorea and V. Miss Joaquim ‘Agnes’. Complete sequence identity was established between V. teres var. andersonii and V. Miss Joaquim ‘Agnes’. The matK sequences obtained from the herbarium specimens of V. teres and V. Miss Joaquim were completely identical to the sequences obtained from the fresh samples of V. teres var. andersonii and V. Miss Joaquim ‘Agnes’. Conclusions The pod parent of V. Miss Joaquim ‘Agnes’ is V. teres var. andersonii and, by exclusion, the pollen parent is V. hookeriana. The herbarium and fresh samples of V. teres var. andersonii and V. Miss Joaquim share the same inferred maternity. The matK gene was more informative than rbcL and facilitated differentiation of varieties of V. teres. PMID:22476488

Influence of Pattern of Missing Data on Performance of Imputation Methods: An Example Using National Data on Drug Injection in Prisons

PubMed Central

Haji-Maghsoudi, Saiedeh; Haghdoost, Ali-akbar; Rastegari, Azam; Baneshi, Mohammad Reza

2013-01-01

Background: Policy makers need models to be able to detect groups at high risk of HIV infection. Incomplete records and dirty data are frequently seen in national data sets. Presence of missing data challenges the practice of model development. Several studies suggested that performance of imputation methods is acceptable when missing rate is moderate. One of the issues which was of less concern, to be addressed here, is the role of the pattern of missing data. Methods: We used information of 2720 prisoners. Results derived from fitting regression model to whole data were served as gold standard. Missing data were then generated so that 10%, 20% and 50% of data were lost. In scenario 1, we generated missing values, at above rates, in one variable which was significant in gold model (age). In scenario 2, a small proportion of each of independent variable was dropped out. Four imputation methods, under different Event Per Variable (EPV) values, were compared in terms of selection of important variables and parameter estimation. Results: In scenario 2, bias in estimates was low and performances of all methods for handing missing data were similar. All methods at all missing rates were able to detect significance of age. In scenario 1, biases in estimations were increased, in particular at 50% missing rate. Here at EPVs of 10 and 5, imputation methods failed to capture effect of age. Conclusion: In scenario 2, all imputation methods at all missing rates, were able to detect age as being significant. This was not the case in scenario 1. Our results showed that performance of imputation methods depends on the pattern of missing data. PMID:24596839

Impact of missing data strategies in studies of parental employment and health: Missing items, missing waves, and missing mothers.

PubMed

Nguyen, Cattram D; Strazdins, Lyndall; Nicholson, Jan M; Cooklin, Amanda R

2018-07-01

Understanding the long-term health effects of employment - a major social determinant - on population health is best understood via longitudinal cohort studies, yet missing data (attrition, item non-response) remain a ubiquitous challenge. Additionally, and unique to the work-family context, is the intermittent participation of parents, particularly mothers, in employment, yielding 'incomplete' data. Missing data are patterned by gender and social circumstances, and the extent and nature of resulting biases are unknown. This study investigates how estimates of the association between work-family conflict and mental health depend on the use of four different approaches to missing data treatment, each of which allows for progressive inclusion of more cases in the analyses. We used 5 waves of data from 4983 mothers participating in the Longitudinal Study of Australian Children. Only 23% had completely observed work-family conflict data across all waves. Participants with and without missing data differed such that complete cases were the most advantaged group. Comparison of the missing data treatments indicate the expected narrowing of confidence intervals when more sample were included. However, impact on the estimated strength of association varied by level of exposure: At the lower levels of work-family conflict, estimates strengthened (were larger); at higher levels they weakened (were smaller). Our results suggest that inadequate handling of missing data in extant longitudinal studies of work-family conflict and mental health may have misestimated the adverse effects of work-family conflict, particularly for mothers. Considerable caution should be exercised in interpreting analyses that fail to explore and account for biases arising from missing data. Copyright © 2018. Published by Elsevier Ltd.

Identification and Validation of Human Missing Proteins and Peptides in Public Proteome Databases: Data Mining Strategy.

PubMed

Elguoshy, Amr; Hirao, Yoshitoshi; Xu, Bo; Saito, Suguru; Quadery, Ali F; Yamamoto, Keiko; Mitsui, Toshiaki; Yamamoto, Tadashi

2017-12-01

In an attempt to complete human proteome project (HPP), Chromosome-Centric Human Proteome Project (C-HPP) launched the journey of missing protein (MP) investigation in 2012. However, 2579 and 572 protein entries in the neXtProt (2017-1) are still considered as missing and uncertain proteins, respectively. Thus, in this study, we proposed a pipeline to analyze, identify, and validate human missing and uncertain proteins in open-access transcriptomics and proteomics databases. Analysis of RNA expression pattern for missing proteins in Human protein Atlas showed that 28% of them, such as Olfactory receptor 1I1 ( O60431 ), had no RNA expression, suggesting the necessity to consider uncommon tissues for transcriptomic and proteomic studies. Interestingly, 21% had elevated expression level in a particular tissue (tissue-enriched proteins), indicating the importance of targeting such proteins in their elevated tissues. Additionally, the analysis of RNA expression level for missing proteins showed that 95% had no or low expression level (0-10 transcripts per million), indicating that low abundance is one of the major obstacles facing the detection of missing proteins. Moreover, missing proteins are predicted to generate fewer predicted unique tryptic peptides than the identified proteins. Searching for these predicted unique tryptic peptides that correspond to missing and uncertain proteins in the experimental peptide list of open-access MS-based databases (PA, GPM) resulted in the detection of 402 missing and 19 uncertain proteins with at least two unique peptides (≥9 aa) at <(5 × 10 -4 )% FDR. Finally, matching the native spectra for the experimentally detected peptides with their SRMAtlas synthetic counterparts at three transition sources (QQQ, QTOF, QTRAP) gave us an opportunity to validate 41 missing proteins by ≥2 proteotypic peptides.

Missing Data in the Field of Otorhinolaryngology and Head & Neck Surgery: Need for Improvement.

PubMed

Netten, Anouk P; Dekker, Friedo W; Rieffe, Carolien; Soede, Wim; Briaire, Jeroen J; Frijns, Johan H M

Clinical studies are often facing missing data. Data can be missing for various reasons, for example, patients moved, certain measurements are only administered in high-risk groups, and patients are unable to attend clinic because of their health status. There are various ways to handle these missing data (e.g., complete cases analyses, mean substitution). Each of these techniques potentially influences both the analyses and the results of a study. The first aim of this structured review was to analyze how often researchers in the field of otorhinolaryngology/head & neck surgery report missing data. The second aim was to systematically describe how researchers handle missing data in their analyses. The third aim was to provide a solution on how to deal with missing data by means of the multiple imputation technique. With this review, we aim to contribute to a higher quality of reporting in otorhinolaryngology research. Clinical studies among the 398 most recently published research articles in three major journals in the field of otorhinolaryngology/head & neck surgery were analyzed based on how researchers reported and handled missing data. Of the 316 clinical studies, 85 studies reported some form of missing data. Of those 85, only a small number (12 studies, 3.8%) actively handled the missingness in their data. The majority of researchers exclude incomplete cases, which results in biased outcomes and a drop in statistical power. Within otorhinolaryngology research, missing data are largely ignored and underreported, and consequently, handled inadequately. This has major impact on the results and conclusions drawn from this research. Based on the outcomes of this review, we provide solutions on how to deal with missing data. To illustrate, we clarify the use of multiple imputation techniques, which recently became widely available in standard statistical programs.

Multi-task Gaussian process for imputing missing data in multi-trait and multi-environment trials.

PubMed

Hori, Tomoaki; Montcho, David; Agbangla, Clement; Ebana, Kaworu; Futakuchi, Koichi; Iwata, Hiroyoshi

2016-11-01

A method based on a multi-task Gaussian process using self-measuring similarity gave increased accuracy for imputing missing phenotypic data in multi-trait and multi-environment trials. Multi-environmental trial (MET) data often encounter the problem of missing data. Accurate imputation of missing data makes subsequent analysis more effective and the results easier to understand. Moreover, accurate imputation may help to reduce the cost of phenotyping for thinned-out lines tested in METs. METs are generally performed for multiple traits that are correlated to each other. Correlation among traits can be useful information for imputation, but single-trait-based methods cannot utilize information shared by traits that are correlated. In this paper, we propose imputation methods based on a multi-task Gaussian process (MTGP) using self-measuring similarity kernels reflecting relationships among traits, genotypes, and environments. This framework allows us to use genetic correlation among multi-trait multi-environment data and also to combine MET data and marker genotype data. We compared the accuracy of three MTGP methods and iterative regularized PCA using rice MET data. Two scenarios for the generation of missing data at various missing rates were considered. The MTGP performed a better imputation accuracy than regularized PCA, especially at high missing rates. Under the 'uniform' scenario, in which missing data arise randomly, inclusion of marker genotype data in the imputation increased the imputation accuracy at high missing rates. Under the 'fiber' scenario, in which missing data arise in all traits for some combinations between genotypes and environments, the inclusion of marker genotype data decreased the imputation accuracy for most traits while increasing the accuracy in a few traits remarkably. The proposed methods will be useful for solving the missing data problem in MET data.

Correlates and predictors of missed nursing care in hospitals.

PubMed

Bragadóttir, Helga; Kalisch, Beatrice J; Tryggvadóttir, Gudný Bergthora

2017-06-01

To identify the contribution of hospital, unit, staff characteristics, staffing adequacy and teamwork to missed nursing care in Iceland hospitals. A recently identified quality indicator for nursing care and patient safety is missed nursing care defined as any standard, required nursing care omitted or significantly delayed, indicating an error of omission. Former studies point to contributing factors to missed nursing care regarding hospital, unit and staff characteristics, perceptions of staffing adequacy as well as nursing teamwork, displayed in the Missed Nursing Care Model. This was a quantitative cross-sectional survey study. The samples were all registered nurses and practical nurses (n = 864) working on 27 medical, surgical and intensive care inpatient units in eight hospitals throughout Iceland. Response rate was 69·3%. Data were collected in March-April 2012 using the combined MISSCARE Survey-Icelandic and the Nursing Teamwork Survey-Icelandic. Descriptive, correlational and regression statistics were used for data analysis. Missed nursing care was significantly related to hospital and unit type, participants' age and role and their perception of adequate staffing and level of teamwork. The multiple regression testing of Model 1 indicated unit type, role, age and staffing adequacy to predict 16% of the variance in missed nursing care. Controlling for unit type, role, age and perceptions of staffing adequacy, the multiple regression testing of Model 2 showed that nursing teamwork predicted an additional 14% of the variance in missed nursing care. The results shed light on the correlates and predictors of missed nursing care in hospitals. This study gives direction as to the development of strategies for decreasing missed nursing care, including ensuring appropriate staffing levels and enhanced teamwork. By identifying contributing factors to missed nursing care, appropriate interventions can be developed and tested. © 2016 John Wiley & Sons Ltd.

Missed Opportunities for Hepatitis A Vaccination, National Immunization Survey-Child, 2013.

PubMed

Casillas, Shannon M; Bednarczyk, Robert A

2017-08-01

To quantify the number of missed opportunities for vaccination with hepatitis A vaccine in children and assess the association of missed opportunities for hepatitis A vaccination with covariates of interest. Weighted data from the 2013 National Immunization Survey of US children aged 19-35 months were used. Analysis was restricted to children with provider-verified vaccination history (n = 13 460). Missed opportunities for vaccination were quantified by determining the number of medical visits a child made when another vaccine was administered during eligibility for hepatitis A vaccine, but hepatitis A vaccine was not administered. Cross-sectional bivariate and multivariate polytomous logistic regression were used to assess the association of missed opportunities for vaccination with child and maternal demographic, socioeconomic, and geographic covariates. In 2013, 85% of children in our study population had initiated the hepatitis A vaccine series, and 60% received 2 or more doses. Children who received zero doses of hepatitis A vaccine had an average of 1.77 missed opportunities for vaccination compared with 0.43 missed opportunities for vaccination in those receiving 2 doses. Children with 2 or more missed opportunities for vaccination initiated the vaccine series 6 months later than children without missed opportunities. In the fully adjusted multivariate model, children who were younger, had ever received WIC benefits, or lived in a state with childcare entry mandates were at a reduced odds for 2 or more missed opportunities for vaccination; children living in the Northeast census region were at an increased odds. Missed opportunities for vaccination likely contribute to the poor coverage for hepatitis A vaccination in children; it is important to understand why children are not receiving the vaccine when eligible. Copyright © 2017 Elsevier Inc. All rights reserved.

Collateral missing value imputation: a new robust missing value estimation algorithm for microarray data.

PubMed

Sehgal, Muhammad Shoaib B; Gondal, Iqbal; Dooley, Laurence S

2005-05-15

Microarray data are used in a range of application areas in biology, although often it contains considerable numbers of missing values. These missing values can significantly affect subsequent statistical analysis and machine learning algorithms so there is a strong motivation to estimate these values as accurately as possible before using these algorithms. While many imputation algorithms have been proposed, more robust techniques need to be developed so that further analysis of biological data can be accurately undertaken. In this paper, an innovative missing value imputation algorithm called collateral missing value estimation (CMVE) is presented which uses multiple covariance-based imputation matrices for the final prediction of missing values. The matrices are computed and optimized using least square regression and linear programming methods. The new CMVE algorithm has been compared with existing estimation techniques including Bayesian principal component analysis imputation (BPCA), least square impute (LSImpute) and K-nearest neighbour (KNN). All these methods were rigorously tested to estimate missing values in three separate non-time series (ovarian cancer based) and one time series (yeast sporulation) dataset. Each method was quantitatively analyzed using the normalized root mean square (NRMS) error measure, covering a wide range of randomly introduced missing value probabilities from 0.01 to 0.2. Experiments were also undertaken on the yeast dataset, which comprised 1.7% actual missing values, to test the hypothesis that CMVE performed better not only for randomly occurring but also for a real distribution of missing values. The results confirmed that CMVE consistently demonstrated superior and robust estimation capability of missing values compared with other methods for both series types of data, for the same order of computational complexity. A concise theoretical framework has also been formulated to validate the improved performance of the CMVE algorithm. The CMVE software is available upon request from the authors.

Cyclists' Anger As Determinant of Near Misses Involving Different Road Users.

PubMed

Marín Puchades, Víctor; Prati, Gabriele; Rondinella, Gianni; De Angelis, Marco; Fassina, Filippo; Fraboni, Federico; Pietrantoni, Luca

2017-01-01

Road anger constitutes one of the determinant factors related to safety outcomes (e.g., accidents, near misses). Although cyclists are considered vulnerable road users due to their relatively high rate of fatalities in traffic, previous research has solely focused on car drivers, and no study has yet investigated the effect of anger on cyclists' safety outcomes. The present research aims to investigate, for the first time, the effects of cycling anger toward different types of road users on near misses involving such road users and near misses in general. Using a daily diary web-based questionnaire, we collected data about daily trips, bicycle use, near misses experienced, cyclist's anger and demographic information from 254 Spanish cyclists. Poisson regression was used to assess the association of cycling anger with near misses, which is a count variable. No relationship was found between general cycling anger and near misses occurrence. Anger toward specific road users had different effects on the probability of near misses with different road users. Anger toward the interaction with car drivers increased the probability of near misses involving cyclists and pedestrians. Anger toward interaction with pedestrians was associated with higher probability of near misses with pedestrians. Anger toward cyclists exerted no effect on the probability of near misses with any road user (i.e., car drivers, cyclists or pedestrians), whereas anger toward the interactions with the police had a diminishing effect on the occurrence of near misses' involving all types of road users. The present study demonstrated that the effect of road anger on safety outcomes among cyclists is different from that of motorists. Moreover, the target of anger played an important role on safety both for the cyclist and the specific road users. Possible explanations for these differences are based on the difference in status and power with motorists, as well as on the potential displaced aggression produced by the fear of retaliation by motorized vehicle users.

An interference account of the missing-VP effect

PubMed Central

Häussler, Jana; Bader, Markus

2015-01-01

Sentences with doubly center-embedded relative clauses in which a verb phrase (VP) is missing are sometimes perceived as grammatical, thus giving rise to an illusion of grammaticality. In this paper, we provide a new account of why missing-VP sentences, which are both complex and ungrammatical, lead to an illusion of grammaticality, the so-called missing-VP effect. We propose that the missing-VP effect in particular, and processing difficulties with multiply center-embedded clauses more generally, are best understood as resulting from interference during cue-based retrieval. When processing a sentence with double center-embedding, a retrieval error due to interference can cause the verb of an embedded clause to be erroneously attached into a higher clause. This can lead to an illusion of grammaticality in the case of missing-VP sentences and to processing complexity in the case of complete sentences with double center-embedding. Evidence for an interference account of the missing-VP effect comes from experiments that have investigated the missing-VP effect in German using a speeded grammaticality judgments procedure. We review this evidence and then present two new experiments that show that the missing-VP effect can be found in German also with less restricting procedures. One experiment was a questionnaire study which required grammaticality judgments from participants without imposing any time constraints. The second experiment used a self-paced reading procedure and did not require any judgments. Both experiments confirm the prior findings of missing-VP effects in German and also show that the missing-VP effect is subject to a primacy effect as known from the memory literature. Based on this evidence, we argue that an account of missing-VP effects in terms of interference during cue-based retrieval is superior to accounts in terms of limited memory resources or in terms of experience with embedded structures. PMID:26136698

Missing data methods for dealing with missing items in quality of life questionnaires. A comparison by simulation of personal mean score, full information maximum likelihood, multiple imputation, and hot deck techniques applied to the SF-36 in the French 2003 decennial health survey.

PubMed

Peyre, Hugo; Leplège, Alain; Coste, Joël

2011-03-01

Missing items are common in quality of life (QoL) questionnaires and present a challenge for research in this field. It remains unclear which of the various methods proposed to deal with missing data performs best in this context. We compared personal mean score, full information maximum likelihood, multiple imputation, and hot deck techniques using various realistic simulation scenarios of item missingness in QoL questionnaires constructed within the framework of classical test theory. Samples of 300 and 1,000 subjects were randomly drawn from the 2003 INSEE Decennial Health Survey (of 23,018 subjects representative of the French population and having completed the SF-36) and various patterns of missing data were generated according to three different item non-response rates (3, 6, and 9%) and three types of missing data (Little and Rubin's "missing completely at random," "missing at random," and "missing not at random"). The missing data methods were evaluated in terms of accuracy and precision for the analysis of one descriptive and one association parameter for three different scales of the SF-36. For all item non-response rates and types of missing data, multiple imputation and full information maximum likelihood appeared superior to the personal mean score and especially to hot deck in terms of accuracy and precision; however, the use of personal mean score was associated with insignificant bias (relative bias <2%) in all studied situations. Whereas multiple imputation and full information maximum likelihood are confirmed as reference methods, the personal mean score appears nonetheless appropriate for dealing with items missing from completed SF-36 questionnaires in most situations of routine use. These results can reasonably be extended to other questionnaires constructed according to classical test theory.

Design, implementation and reporting strategies to reduce the instance and impact of missing patient-reported outcome (PRO) data: a systematic review.

PubMed

Mercieca-Bebber, Rebecca; Palmer, Michael J; Brundage, Michael; Calvert, Melanie; Stockler, Martin R; King, Madeleine T

2016-06-15

Patient-reported outcomes (PROs) provide important information about the impact of treatment from the patients' perspective. However, missing PRO data may compromise the interpretability and value of the findings. We aimed to report: (1) a non-technical summary of problems caused by missing PRO data; and (2) a systematic review by collating strategies to: (A) minimise rates of missing PRO data, and (B) facilitate transparent interpretation and reporting of missing PRO data in clinical research. Our systematic review does not address statistical handling of missing PRO data. MEDLINE and Cumulative Index to Nursing and Allied Health Literature (CINAHL) databases (inception to 31 March 2015), and citing articles and reference lists from relevant sources. English articles providing recommendations for reducing missing PRO data rates, or strategies to facilitate transparent interpretation and reporting of missing PRO data were included. 2 reviewers independently screened articles against eligibility criteria. Discrepancies were resolved with the research team. Recommendations were extracted and coded according to framework synthesis. 117 sources (55% discussion papers, 26% original research) met the eligibility criteria. Design and methodological strategies for reducing rates of missing PRO data included: incorporating PRO-specific information into the protocol; carefully designing PRO assessment schedules and defining termination rules; minimising patient burden; appointing a PRO coordinator; PRO-specific training for staff; ensuring PRO studies are adequately resourced; and continuous quality assurance. Strategies for transparent interpretation and reporting of missing PRO data include utilising auxiliary data to inform analysis; transparently reporting baseline PRO scores, rates and reasons for missing data; and methods for handling missing PRO data. The instance of missing PRO data and its potential to bias clinical research can be minimised by implementing thoughtful design, rigorous methodology and transparent reporting strategies. All members of the research team have a responsibility in implementing such strategies. 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/

"Wish You Were Here": Examining Characteristics, Outcomes, and Statistical Solutions for Missing Cases in Web-Based Psychotherapeutic Trials.

PubMed

Karin, Eyal; Dear, Blake F; Heller, Gillian Z; Crane, Monique F; Titov, Nickolai

2018-04-19

Missing cases following treatment are common in Web-based psychotherapy trials. Without the ability to directly measure and evaluate the outcomes for missing cases, the ability to measure and evaluate the effects of treatment is challenging. Although common, little is known about the characteristics of Web-based psychotherapy participants who present as missing cases, their likely clinical outcomes, or the suitability of different statistical assumptions that can characterize missing cases. Using a large sample of individuals who underwent Web-based psychotherapy for depressive symptoms (n=820), the aim of this study was to explore the characteristics of cases who present as missing cases at posttreatment (n=138), their likely treatment outcomes, and compare between statistical methods for replacing their missing data. First, common participant and treatment features were tested through binary logistic regression models, evaluating the ability to predict missing cases. Second, the same variables were screened for their ability to increase or impede the rate symptom change that was observed following treatment. Third, using recontacted cases at 3-month follow-up to proximally represent missing cases outcomes following treatment, various simulated replacement scores were compared and evaluated against observed clinical follow-up scores. Missing cases were dominantly predicted by lower treatment adherence and increased symptoms at pretreatment. Statistical methods that ignored these characteristics can overlook an important clinical phenomenon and consequently produce inaccurate replacement outcomes, with symptoms estimates that can swing from -32% to 70% from the observed outcomes of recontacted cases. In contrast, longitudinal statistical methods that adjusted their estimates for missing cases outcomes by treatment adherence rates and baseline symptoms scores resulted in minimal measurement bias (<8%). Certain variables can characterize and predict missing cases likelihood and jointly predict lesser clinical improvement. Under such circumstances, individuals with potentially worst off treatment outcomes can become concealed, and failure to adjust for this can lead to substantial clinical measurement bias. Together, this preliminary research suggests that missing cases in Web-based psychotherapeutic interventions may not occur as random events and can be systematically predicted. Critically, at the same time, missing cases may experience outcomes that are distinct and important for a complete understanding of the treatment effect. ©Eyal Karin, Blake F Dear, Gillian Z Heller, Monique F Crane, Nickolai Titov. Originally published in JMIR Mental Health (http://mental.jmir.org), 19.04.2018.

“Wish You Were Here”: Examining Characteristics, Outcomes, and Statistical Solutions for Missing Cases in Web-Based Psychotherapeutic Trials

PubMed Central

Dear, Blake F; Heller, Gillian Z; Crane, Monique F; Titov, Nickolai

2018-01-01

Background Missing cases following treatment are common in Web-based psychotherapy trials. Without the ability to directly measure and evaluate the outcomes for missing cases, the ability to measure and evaluate the effects of treatment is challenging. Although common, little is known about the characteristics of Web-based psychotherapy participants who present as missing cases, their likely clinical outcomes, or the suitability of different statistical assumptions that can characterize missing cases. Objective Using a large sample of individuals who underwent Web-based psychotherapy for depressive symptoms (n=820), the aim of this study was to explore the characteristics of cases who present as missing cases at posttreatment (n=138), their likely treatment outcomes, and compare between statistical methods for replacing their missing data. Methods First, common participant and treatment features were tested through binary logistic regression models, evaluating the ability to predict missing cases. Second, the same variables were screened for their ability to increase or impede the rate symptom change that was observed following treatment. Third, using recontacted cases at 3-month follow-up to proximally represent missing cases outcomes following treatment, various simulated replacement scores were compared and evaluated against observed clinical follow-up scores. Results Missing cases were dominantly predicted by lower treatment adherence and increased symptoms at pretreatment. Statistical methods that ignored these characteristics can overlook an important clinical phenomenon and consequently produce inaccurate replacement outcomes, with symptoms estimates that can swing from −32% to 70% from the observed outcomes of recontacted cases. In contrast, longitudinal statistical methods that adjusted their estimates for missing cases outcomes by treatment adherence rates and baseline symptoms scores resulted in minimal measurement bias (<8%). Conclusions Certain variables can characterize and predict missing cases likelihood and jointly predict lesser clinical improvement. Under such circumstances, individuals with potentially worst off treatment outcomes can become concealed, and failure to adjust for this can lead to substantial clinical measurement bias. Together, this preliminary research suggests that missing cases in Web-based psychotherapeutic interventions may not occur as random events and can be systematically predicted. Critically, at the same time, missing cases may experience outcomes that are distinct and important for a complete understanding of the treatment effect. PMID:29674311

How to deal with missing longitudinal data in cost of illness analysis in Alzheimer's disease-suggestions from the GERAS observational study.

PubMed

Belger, Mark; Haro, Josep Maria; Reed, Catherine; Happich, Michael; Kahle-Wrobleski, Kristin; Argimon, Josep Maria; Bruno, Giuseppe; Dodel, Richard; Jones, Roy W; Vellas, Bruno; Wimo, Anders

2016-07-18

Missing data are a common problem in prospective studies with a long follow-up, and the volume, pattern and reasons for missing data may be relevant when estimating the cost of illness. We aimed to evaluate the effects of different methods for dealing with missing longitudinal cost data and for costing caregiver time on total societal costs in Alzheimer's disease (AD). GERAS is an 18-month observational study of costs associated with AD. Total societal costs included patient health and social care costs, and caregiver health and informal care costs. Missing data were classified as missing completely at random (MCAR), missing at random (MAR) or missing not at random (MNAR). Simulation datasets were generated from baseline data with 10-40 % missing total cost data for each missing data mechanism. Datasets were also simulated to reflect the missing cost data pattern at 18 months using MAR and MNAR assumptions. Naïve and multiple imputation (MI) methods were applied to each dataset and results compared with complete GERAS 18-month cost data. Opportunity and replacement cost approaches were used for caregiver time, which was costed with and without supervision included and with time for working caregivers only being costed. Total costs were available for 99.4 % of 1497 patients at baseline. For MCAR datasets, naïve methods performed as well as MI methods. For MAR, MI methods performed better than naïve methods. All imputation approaches were poor for MNAR data. For all approaches, percentage bias increased with missing data volume. For datasets reflecting 18-month patterns, a combination of imputation methods provided more accurate cost estimates (e.g. bias: -1 % vs -6 % for single MI method), although different approaches to costing caregiver time had a greater impact on estimated costs (29-43 % increase over base case estimate). Methods used to impute missing cost data in AD will impact on accuracy of cost estimates although varying approaches to costing informal caregiver time has the greatest impact on total costs. Tailoring imputation methods to the reason for missing data will further our understanding of the best analytical approach for studies involving cost outcomes.

Missed opportunities for HPV immunization among young adult women

PubMed Central

Oliveira, Carlos R.; Rock, Robert M.; Shapiro, Eugene D.; Xu, Xiao; Lundsberg, Lisbet; Zhang, Liye B.; Gariepy, Aileen; Illuzzi, Jessica L.; Sheth, Sangini S.

2018-01-01

BACKGROUND Despite the availability of a safe and efficacious vaccine against human papillomavirus, uptake of the vaccine in the United States is low. Missed clinical opportunities to recommend and to administer human papillomavirus vaccine are considered one of the most important reasons for its low uptake in adolescents; however, little is known about the frequency or characteristics of missed opportunities in the young adult (18–26 years of age) population. OBJECTIVE The objective of the study was to assess both the rates of and the factors associated with missed opportunities for human papillomavirus immunization among young adult women who attended an urban obstetrics and gynecology clinic. STUDY DESIGN In this cross-sectional study, medical records were reviewed for all women 18–26 years of age who were underimmunized (<3 doses) and who sought care from Feb. 1, 2013, to January 31, 2014, at an urban, hospital-based obstetrics and gynecology clinic. A missed opportunity for human papillomavirus immunization was defined as a clinic visit at which the patient was eligible to receive the vaccine and a dose was due but not administered. Multivariable logistic regression was used to test associations between sociodemographic variables and missed opportunities. RESULTS There were 1670 vaccine-eligible visits by 1241 underimmunized women, with a mean of 1.3 missed opportunities/person. During the study period, 833 of the vaccine eligible women (67.1%) had at least 1 missed opportunity. Overall, the most common types of visits during which a missed opportunity occurred were postpartum visits (17%) or visits for either sexually transmitted disease screening (21%) or contraception (33%). Of the patients with a missed opportunity, 26.5% had a visit at which an injectable medication or a different vaccine was administered. Women who identified their race as black had higher adjusted odds of having a missed opportunity compared with white women (adjusted odds ratio, 1.61 [95% confidence interval, 1.08–2.41], P < .02). Women who reported a non-English- or non-Spanish-preferred language had lower adjusted odds of having a missed opportunity (adjusted odds ratio, 0.25 [95% confidence interval, 0.07–0.87], P = .03). No other patient characteristics assessed in this study were significantly associated with having a missed opportunity. CONCLUSION A majority of young-adult women in this study had missed opportunities for human papillomavirus immunization, and significant racial disparity was observed. The greatest frequency of missed opportunities occurred with visits for either contraception or for sexually transmitted disease screening. PMID:29223597

Treatment of missing data in follow-up studies of randomised controlled trials: A systematic review of the literature.

PubMed

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.

Missing Not at Random Models for Latent Growth Curve Analyses

ERIC Educational Resources Information Center

Enders, Craig K.

2011-01-01

The past decade has seen a noticeable shift in missing data handling techniques that assume a missing at random (MAR) mechanism, where the propensity for missing data on an outcome is related to other analysis variables. Although MAR is often reasonable, there are situations where this assumption is unlikely to hold, leading to biased parameter…

20 CFR 416.1411 - Good cause for missing the deadline to request review.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 20 Employees' Benefits 2 2011-04-01 2011-04-01 false Good cause for missing the deadline to... Reopening of Determinations and Decisions Reconsideration § 416.1411 Good cause for missing the deadline to request review. (a) In determining whether you have shown that you have good cause for missing a deadline...

19 CFR 141.66 - Bond for missing documents.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 19 Customs Duties 2 2011-04-01 2011-04-01 false Bond for missing documents. 141.66 Section 141.66... TREASURY (CONTINUED) ENTRY OF MERCHANDISE Presentation of Entry Papers § 141.66 Bond for missing documents... applicable to incomplete or missing invoices.) [T.D. 73-175, 38 FR 17447, July 2, 1973, as amended by T.D. 84...

17 CFR 240.17f-1 - Requirements for reporting and inquiry with respect to missing, lost, counterfeit or stolen...

Code of Federal Regulations, 2013 CFR

2013-04-01

... inquiry with respect to missing, lost, counterfeit or stolen securities. 240.17f-1 Section 240.17f-1... and inquiry with respect to missing, lost, counterfeit or stolen securities. (a) Definitions. For...). (8) The term missing shall include any securities certificate that: (i) Cannot be located or...

19 CFR 158.4 - Liability of carrier for lost or missing packages.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 19 Customs Duties 2 2012-04-01 2012-04-01 false Liability of carrier for lost or missing packages... EXPORTED Lost or Missing Packages and Deficiencies in Contents of Packages § 158.4 Liability of carrier for lost or missing packages. Upon a joint determination or independent determination of quantity as set...

20 CFR 416.1411 - Good cause for missing the deadline to request review.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 20 Employees' Benefits 2 2012-04-01 2012-04-01 false Good cause for missing the deadline to... Reopening of Determinations and Decisions Reconsideration § 416.1411 Good cause for missing the deadline to request review. (a) In determining whether you have shown that you have good cause for missing a deadline...

19 CFR 141.66 - Bond for missing documents.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 19 Customs Duties 2 2013-04-01 2013-04-01 false Bond for missing documents. 141.66 Section 141.66... TREASURY (CONTINUED) ENTRY OF MERCHANDISE Presentation of Entry Papers § 141.66 Bond for missing documents... applicable to incomplete or missing invoices.) [T.D. 73-175, 38 FR 17447, July 2, 1973, as amended by T.D. 84...

19 CFR 158.4 - Liability of carrier for lost or missing packages.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 19 Customs Duties 2 2013-04-01 2013-04-01 false Liability of carrier for lost or missing packages... EXPORTED Lost or Missing Packages and Deficiencies in Contents of Packages § 158.4 Liability of carrier for lost or missing packages. Upon a joint determination or independent determination of quantity as set...

19 CFR 158.4 - Liability of carrier for lost or missing packages.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 19 Customs Duties 2 2011-04-01 2011-04-01 false Liability of carrier for lost or missing packages... EXPORTED Lost or Missing Packages and Deficiencies in Contents of Packages § 158.4 Liability of carrier for lost or missing packages. Upon a joint determination or independent determination of quantity as set...

20 CFR 416.1411 - Good cause for missing the deadline to request review.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 20 Employees' Benefits 2 2013-04-01 2013-04-01 false Good cause for missing the deadline to... Reopening of Determinations and Decisions Reconsideration § 416.1411 Good cause for missing the deadline to request review. (a) In determining whether you have shown that you have good cause for missing a deadline...

19 CFR 141.66 - Bond for missing documents.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 19 Customs Duties 2 2010-04-01 2010-04-01 false Bond for missing documents. 141.66 Section 141.66... TREASURY (CONTINUED) ENTRY OF MERCHANDISE Presentation of Entry Papers § 141.66 Bond for missing documents... applicable to incomplete or missing invoices.) [T.D. 73-175, 38 FR 17447, July 2, 1973, as amended by T.D. 84...

19 CFR 158.4 - Liability of carrier for lost or missing packages.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 19 Customs Duties 2 2014-04-01 2014-04-01 false Liability of carrier for lost or missing packages... EXPORTED Lost or Missing Packages and Deficiencies in Contents of Packages § 158.4 Liability of carrier for lost or missing packages. Upon a joint determination or independent determination of quantity as set...

19 CFR 158.4 - Liability of carrier for lost or missing packages.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 19 Customs Duties 2 2010-04-01 2010-04-01 false Liability of carrier for lost or missing packages... EXPORTED Lost or Missing Packages and Deficiencies in Contents of Packages § 158.4 Liability of carrier for lost or missing packages. Upon a joint determination or independent determination of quantity as set...

19 CFR 141.66 - Bond for missing documents.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 19 Customs Duties 2 2014-04-01 2014-04-01 false Bond for missing documents. 141.66 Section 141.66... TREASURY (CONTINUED) ENTRY OF MERCHANDISE Presentation of Entry Papers § 141.66 Bond for missing documents... applicable to incomplete or missing invoices.) [T.D. 73-175, 38 FR 17447, July 2, 1973, as amended by T.D. 84...

19 CFR 141.66 - Bond for missing documents.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 19 Customs Duties 2 2012-04-01 2012-04-01 false Bond for missing documents. 141.66 Section 141.66... TREASURY (CONTINUED) ENTRY OF MERCHANDISE Presentation of Entry Papers § 141.66 Bond for missing documents... applicable to incomplete or missing invoices.) [T.D. 73-175, 38 FR 17447, July 2, 1973, as amended by T.D. 84...

17 CFR 240.17f-1 - Requirements for reporting and inquiry with respect to missing, lost, counterfeit or stolen...

Code of Federal Regulations, 2012 CFR

2012-04-01

... inquiry with respect to missing, lost, counterfeit or stolen securities. 240.17f-1 Section 240.17f-1... and inquiry with respect to missing, lost, counterfeit or stolen securities. (a) Definitions. For...). (8) The term missing shall include any securities certificate that: (i) Cannot be located or...

17 CFR 240.17f-1 - Requirements for reporting and inquiry with respect to missing, lost, counterfeit or stolen...

Code of Federal Regulations, 2011 CFR

2011-04-01

... inquiry with respect to missing, lost, counterfeit or stolen securities. 240.17f-1 Section 240.17f-1... and inquiry with respect to missing, lost, counterfeit or stolen securities. (a) Definitions. For...). (8) The term missing shall include any securities certificate that: (i) Cannot be located or...

17 CFR 240.17f-1 - Requirements for reporting and inquiry with respect to missing, lost, counterfeit or stolen...

Code of Federal Regulations, 2014 CFR

2014-04-01

... inquiry with respect to missing, lost, counterfeit or stolen securities. 240.17f-1 Section 240.17f-1... and inquiry with respect to missing, lost, counterfeit or stolen securities. (a) Definitions. For...). (8) The term missing shall include any securities certificate that: (i) Cannot be located or...

20 CFR 416.1411 - Good cause for missing the deadline to request review.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 20 Employees' Benefits 2 2014-04-01 2014-04-01 false Good cause for missing the deadline to... Reopening of Determinations and Decisions Reconsideration § 416.1411 Good cause for missing the deadline to request review. (a) In determining whether you have shown that you have good cause for missing a deadline...

Taking the Missing Propensity into Account When Estimating Competence Scores: Evaluation of Item Response Theory Models for Nonignorable Omissions

ERIC Educational Resources Information Center

Köhler, Carmen; Pohl, Steffi; Carstensen, Claus H.

2015-01-01

When competence tests are administered, subjects frequently omit items. These missing responses pose a threat to correctly estimating the proficiency level. Newer model-based approaches aim to take nonignorable missing data processes into account by incorporating a latent missing propensity into the measurement model. Two assumptions are typically…

77 FR 36404 - Approval and Promulgation of Air Quality Implementation Plans; Massachusetts; Determination of...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-19

... Environmental Protection recently performed a missing data analysis for this site in accordance with the regulatory requirements of 40 CFR Part 50, Appendix I, for both 2010 and 2011. The Massachusetts missing data... the missing days to decisively conclude that on the days with missing ozone data, the ozone levels, if...

45 CFR 1355.40 - Foster care and adoption data collection.

Code of Federal Regulations, 2011 CFR

2011-10-01

.... These are specified in Appendix E to this part. (c) Missing data standards. (1) The term “missing data... missing data. All data which are “out of range” (i.e., the response is beyond the parameters allowed for that particular data element) will also be converted to missing data. Details of the circumstances...

45 CFR 1355.40 - Foster care and adoption data collection.

Code of Federal Regulations, 2010 CFR

2010-10-01

.... These are specified in Appendix E to this part. (c) Missing data standards. (1) The term “missing data... missing data. All data which are “out of range” (i.e., the response is beyond the parameters allowed for that particular data element) will also be converted to missing data. Details of the circumstances...

A Review of Missing Data Handling Methods in Education Research

ERIC Educational Resources Information Center

Cheema, Jehanzeb R.

2014-01-01

Missing data are a common occurrence in survey-based research studies in education, and the way missing values are handled can significantly affect the results of analyses based on such data. Despite known problems with performance of some missing data handling methods, such as mean imputation, many researchers in education continue to use those…

40 CFR 98.335 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... missing data. For the carbon input procedure in § 98.333(b), a complete record of all measured parameters... average carbon contents of inputs according to the procedures in § 98.335(b) if data are missing. (b) For...

40 CFR 98.195 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... estimating missing data. For the procedure in § 98.193(b)(1), a complete record of all measured parameters... available process data or data used for accounting purposes. (b) For missing values related to the CaO and...

77 FR 3147 - Approval and Promulgation of Air Quality Implementation Plans; Delaware, New Jersey, and...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-23

... monitors with missing data. Maximum recorded values are substituted for the missing data. The resulting... which the incomplete site is missing data. The linear regression relationship is based on time periods... between the monitors is used to fill in missing data for the incomplete monitor, so that the normal data...

40 CFR 98.95 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... estimating missing data. (a) Except as provided in paragraph (b) of this section, a complete record of all... required. (b) If you use heat transfer fluids at your facility and are missing data for one or more of the...

40 CFR 98.335 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... missing data. For the carbon input procedure in § 98.333(b), a complete record of all measured parameters... average carbon contents of inputs according to the procedures in § 98.335(b) if data are missing. (b) For...

40 CFR 98.195 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... estimating missing data. For the procedure in § 98.193(b)(1), a complete record of all measured parameters... available process data or data used for accounting purposes. (b) For missing values related to the CaO and...

40 CFR 98.335 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... missing data. For the carbon input procedure in § 98.333(b), a complete record of all measured parameters... average carbon contents of inputs according to the procedures in § 98.335(b) if data are missing. (b) For...

Investigation of Missing Responses in Implementation of Cognitive Diagnostic Models

ERIC Educational Resources Information Center

Dai, Shenghai

2017-01-01

This dissertation is aimed at investigating the impact of missing data and evaluating the performance of five selected methods for handling missing responses in the implementation of Cognitive Diagnostic Models (CDMs). The five methods are: a) treating missing data as incorrect (IN), b) person mean imputation (PM), c) two-way imputation (TW), d)…

40 CFR 98.195 - Procedures for estimating missing data.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Procedures for estimating missing data... estimating missing data. For the procedure in § 98.193(b)(2), a complete record of all measured parameters... process data or data used for accounting purposes. (b) For missing values related to the CaO and MgO...

40 CFR 98.335 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... missing data. For the carbon input procedure in § 98.333(b), a complete record of all measured parameters... average carbon contents of inputs according to the procedures in § 98.335(b) if data are missing. (b) For...

40 CFR 98.195 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... estimating missing data. For the procedure in § 98.193(b)(1), a complete record of all measured parameters... available process data or data used for accounting purposes. (b) For missing values related to the CaO and...

Handling Missing Data in Educational Research Using SPSS

ERIC Educational Resources Information Center

Cheema, Jehanzeb

2012-01-01

This study looked at the effect of a number of factors such as the choice of analytical method, the handling method for missing data, sample size, and proportion of missing data, in order to evaluate the effect of missing data treatment on accuracy of estimation. In order to accomplish this a methodological approach involving simulated data was…

40 CFR 98.335 - Procedures for estimating missing data.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Procedures for estimating missing data... missing data. For the carbon input procedure in § 98.333(b), a complete record of all measured parameters... average carbon contents of inputs according to the procedures in § 98.335(b) if data are missing. (b) For...

The Impact of Five Missing Data Treatments on a Cross-Classified Random Effects Model

ERIC Educational Resources Information Center

Hoelzle, Braden R.

2012-01-01

The present study compared the performance of five missing data treatment methods within a Cross-Classified Random Effects Model environment under various levels and patterns of missing data given a specified sample size. Prior research has shown the varying effect of missing data treatment options within the context of numerous statistical…

Missed Lesions at CT Colonography: Lessons Learned

PubMed Central

Pickhardt, Perry J.

2017-01-01

Misinterpretation at CT colonography (CTC) can result in either a colorectal lesion being missed (false negative) or a false-positive diagnosis. This review will largely focus on potential missed lesions – and ways to avoid such misses. The general causes of false-negative interpretation at CTC can be broadly characterized and grouped into discrete categories related to suboptimal study technique, specific lesion characteristics, anatomic location, and imaging artifacts. Overlapping causes further increase the likelihood of missing a clinically relevant lesion. In the end, if the technical factors of bowel preparation, colonic distention, and robust CTC software are adequately addressed on a consistent basis, and the reader is aware of all the potential pitfalls at CTC, important lesions will seldom be missed. PMID:22539045

Missing incidents in community-dwelling people with dementia: understanding how these dangerous events differ from dementia-related ‘wandering’ is critical to assessment, intervention, and prevention.

PubMed

Rowe, Meredeth A; Greenblum, Catherine A; DʼAoust, Rita F

2012-12-01

At every stage of dementia, people with the condition are at risk for both missing incidents, in which they are unattended and unable to navigate a safe return to their caregiver, and "wandering," a term often used to describe repetitive locomotion with patterns such as lapping or pacing. By understanding the differences between these two phenomena, nurses can teach caregivers how to anticipate and prevent missing incidents, which are not necessarily related to wandering. The authors differentiate missing incidents from wandering, describe personal characteristics that may influence the outcomes in missing incidents, and suggest strategies for preventing and responding to missing incidents.

Compressed sensing based missing nodes prediction in temporal communication network

NASA Astrophysics Data System (ADS)

Cheng, Guangquan; Ma, Yang; Liu, Zhong; Xie, Fuli

2018-02-01

The reconstruction of complex network topology is of great theoretical and practical significance. Most research so far focuses on the prediction of missing links. There are many mature algorithms for link prediction which have achieved good results, but research on the prediction of missing nodes has just begun. In this paper, we propose an algorithm for missing node prediction in complex networks. We detect the position of missing nodes based on their neighbor nodes under the theory of compressed sensing, and extend the algorithm to the case of multiple missing nodes using spectral clustering. Experiments on real public network datasets and simulated datasets show that our algorithm can detect the locations of hidden nodes effectively with high precision.

Maternal near-miss: a multicenter surveillance in Kathmandu Valley.

PubMed

Rana, Ashma; Baral, Gehanath; Dangal, Ganesh

2013-01-01

Multicenter surveillance has been carried out on maternal near-miss in the hospitals with sentinel units. Near-miss is recognized as the predictor of level of care and maternal death. Reducing Maternal Mortality Ratio is one of the challenges to achieve Millennium Development Goal. The objective was to determine the frequency and the nature of near-miss events and to analyze the near-miss morbidities among pregnant women. A prospective surveillance was done for a year in 2012 at nine hospitals in Kathmandu valley. Cases eligible by definition were recorded as a census based on WHO near-miss guideline. Similar questionnaires and dummy tables were used to present the results by non-inferential statistics. Out of 157 cases identified with near-miss rate of 3.8 per 1000 live births, severe complications were postpartum hemorrhage 62 (40%) and preeclampsia-eclampsia 25 (17%). Blood transfusion 102 (65%), ICU admission 85 (54%) and surgery 53 (32%) were common critical interventions. Oxytocin was main uterotonic used both prophylactically and therapeutically at health facilities. Total of 30 (19%) cases arrived at health facility after delivery or abortion. MgSO4 was used in all cases of eclampsia. All laparotomies were performed within three hours of arrival. Near-miss to maternal death ratio was 6:1 and MMR was 62. Study result yielded similar pattern amongst developing countries and same near-miss conditions as the causes of maternal death reported by national statistics. Process indicators qualified the recommended standard of care. The near-miss event could be used as a surrogate marker of maternal death and a window for system level intervention.

The association between nurse staffing and omissions in nursing care: A systematic review.

PubMed

Griffiths, Peter; Recio-Saucedo, Alejandra; Dall'Ora, Chiara; Briggs, Jim; Maruotti, Antonello; Meredith, Paul; Smith, Gary B; Ball, Jane

2018-03-08

To identify nursing care most frequently missed in acute adult inpatient wards and to determine evidence for the association of missed care with nurse staffing. Research has established associations between nurse staffing levels and adverse patient outcomes including in-hospital mortality. However, the causal nature of this relationship is uncertain and omissions of nursing care (referred as missed care, care left undone or rationed care) have been proposed as a factor which may provide a more direct indicator of nurse staffing adequacy. Systematic review. We searched the Cochrane Library, CINAHL, Embase and Medline for quantitative studies of associations between staffing and missed care. We searched key journals, personal libraries and reference lists of articles. Two reviewers independently selected studies. Quality appraisal was based on the National Institute for Health and Care Excellence quality appraisal checklist for studies reporting correlations and associations. Data were abstracted on study design, missed care prevalence and measures of association. Synthesis was narrative. Eighteen studies gave subjective reports of missed care. Seventy-five per cent or more nurses reported omitting some care. Fourteen studies found low nurse staffing levels were significantly associated with higher reports of missed care. There was little evidence that adding support workers to the team reduced missed care. Low Registered Nurse staffing is associated with reports of missed nursing care in hospitals. Missed care is a promising indicator of nurse staffing adequacy. The extent to which the relationships observed represent actual failures, is yet to be investigated. © 2018 The Authors. Journal of Advanced Nursing Published by John Wiley & Sons Ltd.

Application of pattern mixture models to address missing data in longitudinal data analysis using SPSS.

PubMed

Son, Heesook; Friedmann, Erika; Thomas, Sue A

2012-01-01

Longitudinal studies are used in nursing research to examine changes over time in health indicators. Traditional approaches to longitudinal analysis of means, such as analysis of variance with repeated measures, are limited to analyzing complete cases. This limitation can lead to biased results due to withdrawal or data omission bias or to imputation of missing data, which can lead to bias toward the null if data are not missing completely at random. Pattern mixture models are useful to evaluate the informativeness of missing data and to adjust linear mixed model (LMM) analyses if missing data are informative. The aim of this study was to provide an example of statistical procedures for applying a pattern mixture model to evaluate the informativeness of missing data and conduct analyses of data with informative missingness in longitudinal studies using SPSS. The data set from the Patients' and Families' Psychological Response to Home Automated External Defibrillator Trial was used as an example to examine informativeness of missing data with pattern mixture models and to use a missing data pattern in analysis of longitudinal data. Prevention of withdrawal bias, omitted data bias, and bias toward the null in longitudinal LMMs requires the assessment of the informativeness of the occurrence of missing data. Missing data patterns can be incorporated as fixed effects into LMMs to evaluate the contribution of the presence of informative missingness to and control for the effects of missingness on outcomes. Pattern mixture models are a useful method to address the presence and effect of informative missingness in longitudinal studies.

Missing Data in Alcohol Clinical Trials with Binary Outcomes

PubMed Central

Hallgren, Kevin A.; Witkiewitz, Katie; Kranzler, Henry R.; Falk, Daniel E.; Litten, Raye Z.; O’Malley, Stephanie S.; Anton, Raymond F.

2017-01-01

Background Missing data are common in alcohol clinical trials for both continuous and binary endpoints. Approaches to handle missing data have been explored for continuous outcomes, yet no studies have compared missing data approaches for binary outcomes (e.g., abstinence, no heavy drinking days). The present study compares approaches to modeling binary outcomes with missing data in the COMBINE study. Method We included participants in the COMBINE Study who had complete drinking data during treatment and who were assigned to active medication or placebo conditions (N=1146). Using simulation methods, missing data were introduced under common scenarios with varying sample sizes and amounts of missing data. Logistic regression was used to estimate the effect of naltrexone (vs. placebo) in predicting any drinking and any heavy drinking outcomes at the end of treatment using four analytic approaches: complete case analysis (CCA), last observation carried forward (LOCF), the worst-case scenario of missing equals any drinking or heavy drinking (WCS), and multiple imputation (MI). In separate analyses, these approaches were compared when drinking data were manually deleted for those participants who discontinued treatment but continued to provide drinking data. Results WCS produced the greatest amount of bias in treatment effect estimates. MI usually yielded less biased estimates than WCS and CCA in the simulated data, and performed considerably better than LOCF when estimating treatment effects among individuals who discontinued treatment. Conclusions Missing data can introduce bias in treatment effect estimates in alcohol clinical trials. Researchers should utilize modern missing data methods, including MI, and avoid WCS and CCA when analyzing binary alcohol clinical trial outcomes. PMID:27254113

Missing Data in Alcohol Clinical Trials with Binary Outcomes.

PubMed

Hallgren, Kevin A; Witkiewitz, Katie; Kranzler, Henry R; Falk, Daniel E; Litten, Raye Z; O'Malley, Stephanie S; Anton, Raymond F

2016-07-01

Missing data are common in alcohol clinical trials for both continuous and binary end points. Approaches to handle missing data have been explored for continuous outcomes, yet no studies have compared missing data approaches for binary outcomes (e.g., abstinence, no heavy drinking days). This study compares approaches to modeling binary outcomes with missing data in the COMBINE study. We included participants in the COMBINE study who had complete drinking data during treatment and who were assigned to active medication or placebo conditions (N = 1,146). Using simulation methods, missing data were introduced under common scenarios with varying sample sizes and amounts of missing data. Logistic regression was used to estimate the effect of naltrexone (vs. placebo) in predicting any drinking and any heavy drinking outcomes at the end of treatment using 4 analytic approaches: complete case analysis (CCA), last observation carried forward (LOCF), the worst case scenario (WCS) of missing equals any drinking or heavy drinking, and multiple imputation (MI). In separate analyses, these approaches were compared when drinking data were manually deleted for those participants who discontinued treatment but continued to provide drinking data. WCS produced the greatest amount of bias in treatment effect estimates. MI usually yielded less biased estimates than WCS and CCA in the simulated data and performed considerably better than LOCF when estimating treatment effects among individuals who discontinued treatment. Missing data can introduce bias in treatment effect estimates in alcohol clinical trials. Researchers should utilize modern missing data methods, including MI, and avoid WCS and CCA when analyzing binary alcohol clinical trial outcomes. Copyright © 2016 by the Research Society on Alcoholism.

Reporting and dealing with missing quality of life data in RCTs: has the picture changed in the last decade?

PubMed

Fielding, S; Ogbuagu, A; Sivasubramaniam, S; MacLennan, G; Ramsay, C R

2016-12-01

Missing data are a major problem in the analysis of data from randomised trials affecting power and potentially producing biased treatment effects. Specifically focussing on quality of life outcomes, we aimed to report the amount of missing data, whether imputation was used and what methods and was the missing mechanism discussed from four leading medical journals and compare the picture to our previous review nearly a decade ago. A random selection (50 %) of all RCTS published during 2013-2014 in BMJ, JAMA, Lancet and NEJM was obtained. RCTs reported in research letters, cluster RCTs, non-randomised designs, review articles and meta-analysis were excluded. We included 87 RCTs in the review of which 35 % the amount of missing primary QoL data was unclear, 31 (36 %) used imputation. Only 23 % discussed the missing data mechanism. Nearly half used complete case analysis. Reporting was more unclear for secondary QoL outcomes. Compared to the previous review, multiple imputation was used more prominently but mainly in sensitivity analysis. Inadequate reporting and handling of missing QoL data in RCTs are still an issue. There is a large gap between statistical methods research relating to missing data and the use of the methods in applications. A sensitivity analysis should be undertaken to explore the sensitivity of the main results to different missing data assumptions. Medical journals can help to improve the situation by requiring higher standards of reporting and analytical methods to deal with missing data, and by issuing guidance to authors on expected standard.

A comparison of model-based imputation methods for handling missing predictor values in a linear regression model: A simulation study

NASA Astrophysics Data System (ADS)

Hasan, Haliza; Ahmad, Sanizah; Osman, Balkish Mohd; Sapri, Shamsiah; Othman, Nadirah

2017-08-01

In regression analysis, missing covariate data has been a common problem. Many researchers use ad hoc methods to overcome this problem due to the ease of implementation. However, these methods require assumptions about the data that rarely hold in practice. Model-based methods such as Maximum Likelihood (ML) using the expectation maximization (EM) algorithm and Multiple Imputation (MI) are more promising when dealing with difficulties caused by missing data. Then again, inappropriate methods of missing value imputation can lead to serious bias that severely affects the parameter estimates. The main objective of this study is to provide a better understanding regarding missing data concept that can assist the researcher to select the appropriate missing data imputation methods. A simulation study was performed to assess the effects of different missing data techniques on the performance of a regression model. The covariate data were generated using an underlying multivariate normal distribution and the dependent variable was generated as a combination of explanatory variables. Missing values in covariate were simulated using a mechanism called missing at random (MAR). Four levels of missingness (10%, 20%, 30% and 40%) were imposed. ML and MI techniques available within SAS software were investigated. A linear regression analysis was fitted and the model performance measures; MSE, and R-Squared were obtained. Results of the analysis showed that MI is superior in handling missing data with highest R-Squared and lowest MSE when percent of missingness is less than 30%. Both methods are unable to handle larger than 30% level of missingness.

Missed rib fractures on evaluation of initial chest CT for trauma patients: pattern analysis and diagnostic value of coronal multiplanar reconstruction images with multidetector row CT

PubMed Central

Cho, S H; Sung, Y M; Kim, M S

2012-01-01

Objective The objective of this study was to review the prevalence and radiological features of rib fractures missed on initial chest CT evaluation, and to examine the diagnostic value of additional coronal images in a large series of trauma patients. Methods 130 patients who presented to an emergency room for blunt chest trauma underwent multidetector row CT of the thorax within the first hour during their stay, and had follow-up CT or bone scans as diagnostic gold standards. Images were evaluated on two separate occasions: once with axial images and once with both axial and coronal images. The detection rates of missed rib fractures were compared between readings using a non-parametric method of clustered data. In the cases of missed rib fractures, the shapes, locations and associated fractures were evaluated. Results 58 rib fractures were missed with axial images only and 52 were missed with both axial and coronal images (p=0.088). The most common shape of missed rib fractures was buckled (56.9%), and the anterior arc (55.2%) was most commonly involved. 21 (36.2%) missed rib fractures had combined fractures on the same ribs, and 38 (65.5%) were accompanied by fracture on neighbouring ribs. Conclusion Missed rib fractures are not uncommon, and radiologists should be familiar with buckle fractures, which are frequently missed. Additional coronal imagescan be helpful in the diagnosis of rib fractures that are not seen on axial images. PMID:22514102

Missing data in trial-based cost-effectiveness analysis: An incomplete journey.

PubMed

Leurent, Baptiste; Gomes, Manuel; Carpenter, James R

2018-06-01

Cost-effectiveness analyses (CEA) conducted alongside randomised trials provide key evidence for informing healthcare decision making, but missing data pose substantive challenges. Recently, there have been a number of developments in methods and guidelines addressing missing data in trials. However, it is unclear whether these developments have permeated CEA practice. This paper critically reviews the extent of and methods used to address missing data in recently published trial-based CEA. Issues of the Health Technology Assessment journal from 2013 to 2015 were searched. Fifty-two eligible studies were identified. Missing data were very common; the median proportion of trial participants with complete cost-effectiveness data was 63% (interquartile range: 47%-81%). The most common approach for the primary analysis was to restrict analysis to those with complete data (43%), followed by multiple imputation (30%). Half of the studies conducted some sort of sensitivity analyses, but only 2 (4%) considered possible departures from the missing-at-random assumption. Further improvements are needed to address missing data in cost-effectiveness analyses conducted alongside randomised trials. These should focus on limiting the extent of missing data, choosing an appropriate method for the primary analysis that is valid under contextually plausible assumptions, and conducting sensitivity analyses to departures from the missing-at-random assumption. © 2018 The Authors Health Economics published by John Wiley & Sons Ltd.

Restoring method for missing data of spatial structural stress monitoring based on correlation

NASA Astrophysics Data System (ADS)

Zhang, Zeyu; Luo, Yaozhi

2017-07-01

Long-term monitoring of spatial structures is of great importance for the full understanding of their performance and safety. The missing part of the monitoring data link will affect the data analysis and safety assessment of the structure. Based on the long-term monitoring data of the steel structure of the Hangzhou Olympic Center Stadium, the correlation between the stress change of the measuring points is studied, and an interpolation method of the missing stress data is proposed. Stress data of correlated measuring points are selected in the 3 months of the season when missing data is required for fitting correlation. Data of daytime and nighttime are fitted separately for interpolation. For a simple linear regression when single point's correlation coefficient is 0.9 or more, the average error of interpolation is about 5%. For multiple linear regression, the interpolation accuracy is not significantly increased after the number of correlated points is more than 6. Stress baseline value of construction step should be calculated before interpolating missing data in the construction stage, and the average error is within 10%. The interpolation error of continuous missing data is slightly larger than that of the discrete missing data. The data missing rate of this method should better not exceed 30%. Finally, a measuring point's missing monitoring data is restored to verify the validity of the method.

Sex Differences in the Missing-Letter Effect: A Question of Reading or Visual-Spatial Skills?

ERIC Educational Resources Information Center

Saint-Aubin, Jean; Voyer, Daniel; Roy, Macha

2012-01-01

When readers must search for a target letter while reading a continuous text, they are more likely to miss targets in frequent function words than in less frequent content words. This missing-letter effect has been found across many languages, methodologies, and types of reading materials. Despite the ubiquity of the missing-letter effect, sex…

Social Media Use and the Fear of Missing out (FoMO) While Studying Abroad

ERIC Educational Resources Information Center

Hetz, Patricia R.; Dawson, Christi L.; Cullen, Theresa A.

2015-01-01

Fear of Missing Out (FoMO) is a social construct that examines whether students are concerned that they are missing out on experiences that others are having, and we examined this relation to their concerns over missing activities in their home culture. This mixed-methods pilot study sought to determine how social media affects the study abroad…

19 CFR 113.45 - Charge for production of a missing document made against a continuous bond.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 19 Customs Duties 1 2013-04-01 2013-04-01 false Charge for production of a missing document made... Charge for production of a missing document made against a continuous bond. When a continuous bond secures the production of a missing document and the bond is breached by the principal's failure to timely...

20 CFR 408.1011 - How do we determine whether you had good cause for missing the deadline to request review?

Code of Federal Regulations, 2011 CFR

2011-04-01

... cause for missing the deadline to request review? 408.1011 Section 408.1011 Employees' Benefits SOCIAL... missing the deadline to request review? (a) In determining whether you have shown that you have good cause for missing a deadline to request review we consider— (1) What circumstances kept you from making the...

31 CFR 358.19 - Who is responsible for any loss resulting from the conversion of a bearer corpus missing callable...

Code of Federal Regulations, 2012 CFR

2012-07-01

... resulting from the conversion of a bearer corpus missing callable coupons? 358.19 Section 358.19 Money and... corpus missing callable coupons? The submitting depository institution shall indemnify the United States against any loss resulting from the conversion of a bearer corpus that is missing one or more associated...

19 CFR 113.45 - Charge for production of a missing document made against a continuous bond.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 19 Customs Duties 1 2010-04-01 2010-04-01 false Charge for production of a missing document made... Charge for production of a missing document made against a continuous bond. When a continuous bond secures the production of a missing document and the bond is breached by the principal's failure to timely...

29 CFR Appendix A to Part 4050 - Examples of Designated Benefit Determinations for Missing Participants Under § 4050.5 in Plans...

Code of Federal Regulations, 2011 CFR

2011-07-01

... 29 Labor 9 2011-07-01 2011-07-01 false Examples of Designated Benefit Determinations for Missing... PLAN TERMINATIONS MISSING PARTICIPANTS Pt. 4050, App. A Appendix A to Part 4050—Examples of Designated Benefit Determinations for Missing Participants Under § 4050.5 in Plans With Deemed Distribution Dates on...

19 CFR 158.3 - Allowance for lost or missing packages included in an entry summary.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 19 Customs Duties 2 2012-04-01 2012-04-01 false Allowance for lost or missing packages included in..., DAMAGED, ABANDONED, OR EXPORTED Lost or Missing Packages and Deficiencies in Contents of Packages § 158.3 Allowance for lost or missing packages included in an entry summary. Allowance shall be made in the...

31 CFR 358.19 - Who is responsible for any loss resulting from the conversion of a bearer corpus missing callable...

Code of Federal Regulations, 2011 CFR

2011-07-01

... resulting from the conversion of a bearer corpus missing callable coupons? 358.19 Section 358.19 Money and... corpus missing callable coupons? The submitting depository institution shall indemnify the United States against any loss resulting from the conversion of a bearer corpus that is missing one or more associated...

20 CFR 408.1011 - How do we determine whether you had good cause for missing the deadline to request review?

Code of Federal Regulations, 2013 CFR

2013-04-01

... cause for missing the deadline to request review? 408.1011 Section 408.1011 Employees' Benefits SOCIAL... missing the deadline to request review? (a) In determining whether you have shown that you have good cause for missing a deadline to request review we consider— (1) What circumstances kept you from making the...

The Effects of Methods of Imputation for Missing Values on the Validity and Reliability of Scales

ERIC Educational Resources Information Center

Cokluk, Omay; Kayri, Murat

2011-01-01

The main aim of this study is the comparative examination of the factor structures, corrected item-total correlations, and Cronbach-alpha internal consistency coefficients obtained by different methods used in imputation for missing values in conditions of not having missing values, and having missing values of different rates in terms of testing…

31 CFR 358.19 - Who is responsible for any loss resulting from the conversion of a bearer corpus missing callable...

Code of Federal Regulations, 2010 CFR

2010-07-01

... resulting from the conversion of a bearer corpus missing callable coupons? 358.19 Section 358.19 Money and... corpus missing callable coupons? The submitting depository institution shall indemnify the United States against any loss resulting from the conversion of a bearer corpus that is missing one or more associated...

19 CFR 113.45 - Charge for production of a missing document made against a continuous bond.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 19 Customs Duties 1 2012-04-01 2012-04-01 false Charge for production of a missing document made... Charge for production of a missing document made against a continuous bond. When a continuous bond secures the production of a missing document and the bond is breached by the principal's failure to timely...

31 CFR 358.19 - Who is responsible for any loss resulting from the conversion of a bearer corpus missing callable...

Code of Federal Regulations, 2014 CFR

2014-07-01

... resulting from the conversion of a bearer corpus missing callable coupons? 358.19 Section 358.19 Money and... corpus missing callable coupons? The submitting depository institution shall indemnify the United States against any loss resulting from the conversion of a bearer corpus that is missing one or more associated...

19 CFR 113.45 - Charge for production of a missing document made against a continuous bond.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 19 Customs Duties 1 2011-04-01 2011-04-01 false Charge for production of a missing document made... Charge for production of a missing document made against a continuous bond. When a continuous bond secures the production of a missing document and the bond is breached by the principal's failure to timely...

20 CFR 364.5 - Further study of the use of penalty mail in the location and recovery of missing children.

Code of Federal Regulations, 2013 CFR

2013-04-01

... the location and recovery of missing children. 364.5 Section 364.5 Employees' Benefits RAILROAD... AND RECOVERY OF MISSING CHILDREN § 364.5 Further study of the use of penalty mail in the location and recovery of missing children. (a) Criteria. The Board shall continue to study different alternatives for...

20 CFR 364.5 - Further study of the use of penalty mail in the location and recovery of missing children.

Code of Federal Regulations, 2010 CFR

2010-04-01

... the location and recovery of missing children. 364.5 Section 364.5 Employees' Benefits RAILROAD... AND RECOVERY OF MISSING CHILDREN § 364.5 Further study of the use of penalty mail in the location and recovery of missing children. (a) Criteria. The Board shall continue to study different alternatives for...

29 CFR Appendix A to Part 4050 - Examples of Designated Benefit Determinations for Missing Participants Under § 4050.5 in Plans...

Code of Federal Regulations, 2014 CFR

2014-07-01

... 29 Labor 9 2014-07-01 2014-07-01 false Examples of Designated Benefit Determinations for Missing... PLAN TERMINATIONS MISSING PARTICIPANTS Pt. 4050, App. A Appendix A to Part 4050—Examples of Designated Benefit Determinations for Missing Participants Under § 4050.5 in Plans With Deemed Distribution Dates on...

19 CFR 113.45 - Charge for production of a missing document made against a continuous bond.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 19 Customs Duties 1 2014-04-01 2014-04-01 false Charge for production of a missing document made... Charge for production of a missing document made against a continuous bond. When a continuous bond secures the production of a missing document and the bond is breached by the principal's failure to timely...

31 CFR 358.19 - Who is responsible for any loss resulting from the conversion of a bearer corpus missing callable...

Code of Federal Regulations, 2013 CFR

2013-07-01

... resulting from the conversion of a bearer corpus missing callable coupons? 358.19 Section 358.19 Money and... corpus missing callable coupons? The submitting depository institution shall indemnify the United States against any loss resulting from the conversion of a bearer corpus that is missing one or more associated...

29 CFR Appendix A to Part 4050 - Examples of Designated Benefit Determinations for Missing Participants Under § 4050.5 in Plans...

Code of Federal Regulations, 2012 CFR

2012-07-01

... 29 Labor 9 2012-07-01 2012-07-01 false Examples of Designated Benefit Determinations for Missing... PLAN TERMINATIONS MISSING PARTICIPANTS Pt. 4050, App. A Appendix A to Part 4050—Examples of Designated Benefit Determinations for Missing Participants Under § 4050.5 in Plans With Deemed Distribution Dates on...

20 CFR 364.5 - Further study of the use of penalty mail in the location and recovery of missing children.

Code of Federal Regulations, 2011 CFR

2011-04-01

... the location and recovery of missing children. 364.5 Section 364.5 Employees' Benefits RAILROAD... AND RECOVERY OF MISSING CHILDREN § 364.5 Further study of the use of penalty mail in the location and recovery of missing children. (a) Criteria. The Board shall continue to study different alternatives for...

20 CFR 364.5 - Further study of the use of penalty mail in the location and recovery of missing children.

Code of Federal Regulations, 2012 CFR

2012-04-01

... the location and recovery of missing children. 364.5 Section 364.5 Employees' Benefits RAILROAD... AND RECOVERY OF MISSING CHILDREN § 364.5 Further study of the use of penalty mail in the location and recovery of missing children. (a) Criteria. The Board shall continue to study different alternatives for...

29 CFR Appendix A to Part 4050 - Examples of Designated Benefit Determinations for Missing Participants Under § 4050.5 in Plans...

Code of Federal Regulations, 2013 CFR

2013-07-01

... 29 Labor 9 2013-07-01 2013-07-01 false Examples of Designated Benefit Determinations for Missing... PLAN TERMINATIONS MISSING PARTICIPANTS Pt. 4050, App. A Appendix A to Part 4050—Examples of Designated Benefit Determinations for Missing Participants Under § 4050.5 in Plans With Deemed Distribution Dates on...

19 CFR 158.3 - Allowance for lost or missing packages included in an entry summary.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 19 Customs Duties 2 2013-04-01 2013-04-01 false Allowance for lost or missing packages included in..., DAMAGED, ABANDONED, OR EXPORTED Lost or Missing Packages and Deficiencies in Contents of Packages § 158.3 Allowance for lost or missing packages included in an entry summary. Allowance shall be made in the...

20 CFR 408.1011 - How do we determine whether you had good cause for missing the deadline to request review?

Code of Federal Regulations, 2012 CFR

2012-04-01

... cause for missing the deadline to request review? 408.1011 Section 408.1011 Employees' Benefits SOCIAL... missing the deadline to request review? (a) In determining whether you have shown that you have good cause for missing a deadline to request review we consider— (1) What circumstances kept you from making the...

20 CFR 408.1011 - How do we determine whether you had good cause for missing the deadline to request review?

Code of Federal Regulations, 2014 CFR

2014-04-01

... cause for missing the deadline to request review? 408.1011 Section 408.1011 Employees' Benefits SOCIAL... missing the deadline to request review? (a) In determining whether you have shown that you have good cause for missing a deadline to request review we consider— (1) What circumstances kept you from making the...

19 CFR 158.3 - Allowance for lost or missing packages included in an entry summary.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 19 Customs Duties 2 2010-04-01 2010-04-01 false Allowance for lost or missing packages included in..., DAMAGED, ABANDONED, OR EXPORTED Lost or Missing Packages and Deficiencies in Contents of Packages § 158.3 Allowance for lost or missing packages included in an entry summary. Allowance shall be made in the...

20 CFR 364.5 - Further study of the use of penalty mail in the location and recovery of missing children.

Code of Federal Regulations, 2014 CFR

2014-04-01

... the location and recovery of missing children. 364.5 Section 364.5 Employees' Benefits RAILROAD... AND RECOVERY OF MISSING CHILDREN § 364.5 Further study of the use of penalty mail in the location and recovery of missing children. (a) Criteria. The Board shall continue to study different alternatives for...

19 CFR 158.3 - Allowance for lost or missing packages included in an entry summary.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 19 Customs Duties 2 2011-04-01 2011-04-01 false Allowance for lost or missing packages included in..., DAMAGED, ABANDONED, OR EXPORTED Lost or Missing Packages and Deficiencies in Contents of Packages § 158.3 Allowance for lost or missing packages included in an entry summary. Allowance shall be made in the...

19 CFR 158.3 - Allowance for lost or missing packages included in an entry summary.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 19 Customs Duties 2 2014-04-01 2014-04-01 false Allowance for lost or missing packages included in..., DAMAGED, ABANDONED, OR EXPORTED Lost or Missing Packages and Deficiencies in Contents of Packages § 158.3 Allowance for lost or missing packages included in an entry summary. Allowance shall be made in the...

SEM with Missing Data and Unknown Population Distributions Using Two-Stage ML: Theory and Its Application

ERIC Educational Resources Information Center

Yuan, Ke-Hai; Lu, Laura

2008-01-01

This article provides the theory and application of the 2-stage maximum likelihood (ML) procedure for structural equation modeling (SEM) with missing data. The validity of this procedure does not require the assumption of a normally distributed population. When the population is normally distributed and all missing data are missing at random…

Suspended Education in Massachusetts: Using Days of Lost Instruction Due to Suspension to Evaluate Our Schools

ERIC Educational Resources Information Center

Losen, Daniel J.; Sun, Wei-Ling; Keith, Michael A., II

2017-01-01

Missed instruction can have a devastating impact on educational outcomes. Some reasons for missed instruction are beyond the control of schools and districts: some students miss school due to mental or physical illness or injury, and transportation problems sometimes are to blame. One major reason for missed instruction that schools can directly…

Outlier Removal in Model-Based Missing Value Imputation for Medical Datasets.

PubMed

Huang, Min-Wei; Lin, Wei-Chao; Tsai, Chih-Fong

2018-01-01

Many real-world medical datasets contain some proportion of missing (attribute) values. In general, missing value imputation can be performed to solve this problem, which is to provide estimations for the missing values by a reasoning process based on the (complete) observed data. However, if the observed data contain some noisy information or outliers, the estimations of the missing values may not be reliable or may even be quite different from the real values. The aim of this paper is to examine whether a combination of instance selection from the observed data and missing value imputation offers better performance than performing missing value imputation alone. In particular, three instance selection algorithms, DROP3, GA, and IB3, and three imputation algorithms, KNNI, MLP, and SVM, are used in order to find out the best combination. The experimental results show that that performing instance selection can have a positive impact on missing value imputation over the numerical data type of medical datasets, and specific combinations of instance selection and imputation methods can improve the imputation results over the mixed data type of medical datasets. However, instance selection does not have a definitely positive impact on the imputation result for categorical medical datasets.

Inverse-Probability-Weighted Estimation for Monotone and Nonmonotone Missing Data.

PubMed

Sun, BaoLuo; Perkins, Neil J; Cole, Stephen R; Harel, Ofer; Mitchell, Emily M; Schisterman, Enrique F; Tchetgen Tchetgen, Eric J

2018-03-01

Missing data is a common occurrence in epidemiologic research. In this paper, 3 data sets with induced missing values from the Collaborative Perinatal Project, a multisite US study conducted from 1959 to 1974, are provided as examples of prototypical epidemiologic studies with missing data. Our goal was to estimate the association of maternal smoking behavior with spontaneous abortion while adjusting for numerous confounders. At the same time, we did not necessarily wish to evaluate the joint distribution among potentially unobserved covariates, which is seldom the subject of substantive scientific interest. The inverse probability weighting (IPW) approach preserves the semiparametric structure of the underlying model of substantive interest and clearly separates the model of substantive interest from the model used to account for the missing data. However, IPW often will not result in valid inference if the missing-data pattern is nonmonotone, even if the data are missing at random. We describe a recently proposed approach to modeling nonmonotone missing-data mechanisms under missingness at random to use in constructing the weights in IPW complete-case estimation, and we illustrate the approach using 3 data sets described in a companion article (Am J Epidemiol. 2018;187(3):568-575).

Missing data may lead to changes in hip fracture database studies: a study of the American College of Surgeons National Surgical Quality Improvement Program.

PubMed

Basques, B A; McLynn, R P; Lukasiewicz, A M; Samuel, A M; Bohl, D D; Grauer, J N

2018-02-01

The aims of this study were to characterize the frequency of missing data in the National Surgical Quality Improvement Program (NSQIP) database and to determine how missing data can influence the results of studies dealing with elderly patients with a fracture of the hip. Patients who underwent surgery for a fracture of the hip between 2005 and 2013 were identified from the NSQIP database and the percentage of missing data was noted for demographics, comorbidities and laboratory values. These variables were tested for association with 'any adverse event' using multivariate regressions based on common ways of handling missing data. A total of 26 066 patients were identified. The rate of missing data was up to 77.9% for many variables. Multivariate regressions comparing three methods of handling missing data found different risk factors for postoperative adverse events. Only seven of 35 identified risk factors (20%) were common to all three analyses. Missing data is an important issue in national database studies that researchers must consider when evaluating such investigations. Cite this article: Bone Joint J 2018;100-B:226-32. ©2018 The British Editorial Society of Bone & Joint Surgery.

Should multiple imputation be the method of choice for handling missing data in randomized trials?

PubMed Central

Sullivan, Thomas R; White, Ian R; Salter, Amy B; Ryan, Philip; Lee, Katherine J

2016-01-01

The use of multiple imputation has increased markedly in recent years, and journal reviewers may expect to see multiple imputation used to handle missing data. However in randomized trials, where treatment group is always observed and independent of baseline covariates, other approaches may be preferable. Using data simulation we evaluated multiple imputation, performed both overall and separately by randomized group, across a range of commonly encountered scenarios. We considered both missing outcome and missing baseline data, with missing outcome data induced under missing at random mechanisms. Provided the analysis model was correctly specified, multiple imputation produced unbiased treatment effect estimates, but alternative unbiased approaches were often more efficient. When the analysis model overlooked an interaction effect involving randomized group, multiple imputation produced biased estimates of the average treatment effect when applied to missing outcome data, unless imputation was performed separately by randomized group. Based on these results, we conclude that multiple imputation should not be seen as the only acceptable way to handle missing data in randomized trials. In settings where multiple imputation is adopted, we recommend that imputation is carried out separately by randomized group. PMID:28034175

Should multiple imputation be the method of choice for handling missing data in randomized trials?

PubMed

Sullivan, Thomas R; White, Ian R; Salter, Amy B; Ryan, Philip; Lee, Katherine J

2016-01-01

The use of multiple imputation has increased markedly in recent years, and journal reviewers may expect to see multiple imputation used to handle missing data. However in randomized trials, where treatment group is always observed and independent of baseline covariates, other approaches may be preferable. Using data simulation we evaluated multiple imputation, performed both overall and separately by randomized group, across a range of commonly encountered scenarios. We considered both missing outcome and missing baseline data, with missing outcome data induced under missing at random mechanisms. Provided the analysis model was correctly specified, multiple imputation produced unbiased treatment effect estimates, but alternative unbiased approaches were often more efficient. When the analysis model overlooked an interaction effect involving randomized group, multiple imputation produced biased estimates of the average treatment effect when applied to missing outcome data, unless imputation was performed separately by randomized group. Based on these results, we conclude that multiple imputation should not be seen as the only acceptable way to handle missing data in randomized trials. In settings where multiple imputation is adopted, we recommend that imputation is carried out separately by randomized group.

Inverse-Probability-Weighted Estimation for Monotone and Nonmonotone Missing Data

PubMed Central

Sun, BaoLuo; Perkins, Neil J; Cole, Stephen R; Harel, Ofer; Mitchell, Emily M; Schisterman, Enrique F; Tchetgen Tchetgen, Eric J

2018-01-01

Abstract Missing data is a common occurrence in epidemiologic research. In this paper, 3 data sets with induced missing values from the Collaborative Perinatal Project, a multisite US study conducted from 1959 to 1974, are provided as examples of prototypical epidemiologic studies with missing data. Our goal was to estimate the association of maternal smoking behavior with spontaneous abortion while adjusting for numerous confounders. At the same time, we did not necessarily wish to evaluate the joint distribution among potentially unobserved covariates, which is seldom the subject of substantive scientific interest. The inverse probability weighting (IPW) approach preserves the semiparametric structure of the underlying model of substantive interest and clearly separates the model of substantive interest from the model used to account for the missing data. However, IPW often will not result in valid inference if the missing-data pattern is nonmonotone, even if the data are missing at random. We describe a recently proposed approach to modeling nonmonotone missing-data mechanisms under missingness at random to use in constructing the weights in IPW complete-case estimation, and we illustrate the approach using 3 data sets described in a companion article (Am J Epidemiol. 2018;187(3):568–575). PMID:29165557

Multiple imputation by chained equations for systematically and sporadically missing multilevel data.

PubMed

Resche-Rigon, Matthieu; White, Ian R

2018-06-01

In multilevel settings such as individual participant data meta-analysis, a variable is 'systematically missing' if it is wholly missing in some clusters and 'sporadically missing' if it is partly missing in some clusters. Previously proposed methods to impute incomplete multilevel data handle either systematically or sporadically missing data, but frequently both patterns are observed. We describe a new multiple imputation by chained equations (MICE) algorithm for multilevel data with arbitrary patterns of systematically and sporadically missing variables. The algorithm is described for multilevel normal data but can easily be extended for other variable types. We first propose two methods for imputing a single incomplete variable: an extension of an existing method and a new two-stage method which conveniently allows for heteroscedastic data. We then discuss the difficulties of imputing missing values in several variables in multilevel data using MICE, and show that even the simplest joint multilevel model implies conditional models which involve cluster means and heteroscedasticity. However, a simulation study finds that the proposed methods can be successfully combined in a multilevel MICE procedure, even when cluster means are not included in the imputation models.

A Spatiotemporal Prediction Framework for Air Pollution Based on Deep RNN

NASA Astrophysics Data System (ADS)

Fan, J.; Li, Q.; Hou, J.; Feng, X.; Karimian, H.; Lin, S.

2017-10-01

Time series data in practical applications always contain missing values due to sensor malfunction, network failure, outliers etc. In order to handle missing values in time series, as well as the lack of considering temporal properties in machine learning models, we propose a spatiotemporal prediction framework based on missing value processing algorithms and deep recurrent neural network (DRNN). By using missing tag and missing interval to represent time series patterns, we implement three different missing value fixing algorithms, which are further incorporated into deep neural network that consists of LSTM (Long Short-term Memory) layers and fully connected layers. Real-world air quality and meteorological datasets (Jingjinji area, China) are used for model training and testing. Deep feed forward neural networks (DFNN) and gradient boosting decision trees (GBDT) are trained as baseline models against the proposed DRNN. Performances of three missing value fixing algorithms, as well as different machine learning models are evaluated and analysed. Experiments show that the proposed DRNN framework outperforms both DFNN and GBDT, therefore validating the capacity of the proposed framework. Our results also provides useful insights for better understanding of different strategies that handle missing values.

Recurrent Neural Networks for Multivariate Time Series with Missing Values.

PubMed

Che, Zhengping; Purushotham, Sanjay; Cho, Kyunghyun; Sontag, David; Liu, Yan

2018-04-17

Multivariate time series data in practical applications, such as health care, geoscience, and biology, are characterized by a variety of missing values. In time series prediction and other related tasks, it has been noted that missing values and their missing patterns are often correlated with the target labels, a.k.a., informative missingness. There is very limited work on exploiting the missing patterns for effective imputation and improving prediction performance. In this paper, we develop novel deep learning models, namely GRU-D, as one of the early attempts. GRU-D is based on Gated Recurrent Unit (GRU), a state-of-the-art recurrent neural network. It takes two representations of missing patterns, i.e., masking and time interval, and effectively incorporates them into a deep model architecture so that it not only captures the long-term temporal dependencies in time series, but also utilizes the missing patterns to achieve better prediction results. Experiments of time series classification tasks on real-world clinical datasets (MIMIC-III, PhysioNet) and synthetic datasets demonstrate that our models achieve state-of-the-art performance and provide useful insights for better understanding and utilization of missing values in time series analysis.

Near miss and minor occupational injury: Does it share a common causal pathway with major injury?

PubMed

Alamgir, Hasanat; Yu, Shicheng; Gorman, Erin; Ngan, Karen; Guzman, Jaime

2009-01-01

An essential assumption of injury prevention programs is the common cause hypothesis that the causal pathways of near misses and minor injuries are similar to those of major injuries. The rates of near miss, minor injury and major injury of all reported incidents and musculoskeletal incidents (MSIs) were calculated for three health regions using information from a surveillance database and productive hours from payroll data. The relative distribution of individual causes and activities involved in near miss, minor injury and major injury were then compared. For all reported incidents, there were significant differences in the relative distribution of causes for near miss, minor, and major injury. However, the relative distribution of causes and activities involved in minor and major MSIs were similar. The top causes and activities involved were the same across near miss, minor, and major injury. Finding from this study support the use of near miss and minor injury data as potential outcome measures for injury prevention programs. (c) 2008 Wiley-Liss, Inc.

Multiple imputation for multivariate data with missing and below-threshold measurements: time-series concentrations of pollutants in the Arctic.

PubMed

Hopke, P K; Liu, C; Rubin, D B

2001-03-01

Many chemical and environmental data sets are complicated by the existence of fully missing values or censored values known to lie below detection thresholds. For example, week-long samples of airborne particulate matter were obtained at Alert, NWT, Canada, between 1980 and 1991, where some of the concentrations of 24 particulate constituents were coarsened in the sense of being either fully missing or below detection limits. To facilitate scientific analysis, it is appealing to create complete data by filling in missing values so that standard complete-data methods can be applied. We briefly review commonly used strategies for handling missing values and focus on the multiple-imputation approach, which generally leads to valid inferences when faced with missing data. Three statistical models are developed for multiply imputing the missing values of airborne particulate matter. We expect that these models are useful for creating multiple imputations in a variety of incomplete multivariate time series data sets.

Imputation of missing data in time series for air pollutants

NASA Astrophysics Data System (ADS)

Junger, W. L.; Ponce de Leon, A.

2015-02-01

Missing data are major concerns in epidemiological studies of the health effects of environmental air pollutants. This article presents an imputation-based method that is suitable for multivariate time series data, which uses the EM algorithm under the assumption of normal distribution. Different approaches are considered for filtering the temporal component. A simulation study was performed to assess validity and performance of proposed method in comparison with some frequently used methods. Simulations showed that when the amount of missing data was as low as 5%, the complete data analysis yielded satisfactory results regardless of the generating mechanism of the missing data, whereas the validity began to degenerate when the proportion of missing values exceeded 10%. The proposed imputation method exhibited good accuracy and precision in different settings with respect to the patterns of missing observations. Most of the imputations obtained valid results, even under missing not at random. The methods proposed in this study are implemented as a package called mtsdi for the statistical software system R.

Medical surgical nurses describe missed nursing care tasks-Evaluating our work environment.

PubMed

Winsett, Rebecca P; Rottet, Kendra; Schmitt, Abby; Wathen, Ellen; Wilson, Debra

2016-11-01

The purpose of the study was to explore the nurse work environment by evaluating the self-report of missed nursing care and the reasons for the missed care. A convenience sample of medical surgical nurses from four hospitals was invited to complete the survey for this descriptive study. The sample included 168 nurses. The MISSCARE survey assessed the frequency and reason of 24 routine nursing care elements. The most frequently reported missed care was ambulation as ordered, medications given within a 30 minute window, and mouth care. Moderate or significant reasons reported for the missed care were: unexpected rise in volume/acuity, heavy admissions/discharges, inadequate assistants, inadequate staff, meds not available when needed, and urgent situations. Identifying missed nursing care and reasons for missed care provides an opportunity for exploring strategies to reduce interruptions, develop unit cohesiveness, improve the nurse work environment, and ultimately leading to improved patient outcomes. Copyright © 2016 Elsevier Inc. All rights reserved.

Order-restricted inference for means with missing values.

PubMed

Wang, Heng; Zhong, Ping-Shou

2017-09-01

Missing values appear very often in many applications, but the problem of missing values has not received much attention in testing order-restricted alternatives. Under the missing at random (MAR) assumption, we impute the missing values nonparametrically using kernel regression. For data with imputation, the classical likelihood ratio test designed for testing the order-restricted means is no longer applicable since the likelihood does not exist. This article proposes a novel method for constructing test statistics for assessing means with an increasing order or a decreasing order based on jackknife empirical likelihood (JEL) ratio. It is shown that the JEL ratio statistic evaluated under the null hypothesis converges to a chi-bar-square distribution, whose weights depend on missing probabilities and nonparametric imputation. Simulation study shows that the proposed test performs well under various missing scenarios and is robust for normally and nonnormally distributed data. The proposed method is applied to an Alzheimer's disease neuroimaging initiative data set for finding a biomarker for the diagnosis of the Alzheimer's disease. © 2017, The International Biometric Society.

Statistical approaches to account for missing values in accelerometer data: Applications to modeling physical activity.

PubMed

Yue Xu, Selene; Nelson, Sandahl; Kerr, Jacqueline; Godbole, Suneeta; Patterson, Ruth; Merchant, Gina; Abramson, Ian; Staudenmayer, John; Natarajan, Loki

2018-04-01

Physical inactivity is a recognized risk factor for many chronic diseases. Accelerometers are increasingly used as an objective means to measure daily physical activity. One challenge in using these devices is missing data due to device nonwear. We used a well-characterized cohort of 333 overweight postmenopausal breast cancer survivors to examine missing data patterns of accelerometer outputs over the day. Based on these observed missingness patterns, we created psuedo-simulated datasets with realistic missing data patterns. We developed statistical methods to design imputation and variance weighting algorithms to account for missing data effects when fitting regression models. Bias and precision of each method were evaluated and compared. Our results indicated that not accounting for missing data in the analysis yielded unstable estimates in the regression analysis. Incorporating variance weights and/or subject-level imputation improved precision by >50%, compared to ignoring missing data. We recommend that these simple easy-to-implement statistical tools be used to improve analysis of accelerometer data.

Strategies for Dealing with Missing Data in Clinical Trials: From Design to Analysis

PubMed Central

Dziura, James D.; Post, Lori A.; Zhao, Qing; Fu, Zhixuan; Peduzzi, Peter

2013-01-01

Randomized clinical trials are the gold standard for evaluating interventions as randomized assignment equalizes known and unknown characteristics between intervention groups. However, when participants miss visits, the ability to conduct an intent-to-treat analysis and draw conclusions about a causal link is compromised. As guidance to those performing clinical trials, this review is a non-technical overview of the consequences of missing data and a prescription for its treatment beyond the typical analytic approaches to the entire research process. Examples of bias from incorrect analysis with missing data and discussion of the advantages/disadvantages of analytic methods are given. As no single analysis is definitive when missing data occurs, strategies for its prevention throughout the course of a trial are presented. We aim to convey an appreciation for how missing data influences results and an understanding of the need for careful consideration of missing data during the design, planning, conduct, and analytic stages. PMID:24058309

Spacecraft intercept guidance using zero effort miss steering

NASA Astrophysics Data System (ADS)

Newman, Brett

The suitability of proportional navigation, or an equivalent zero effort miss formulation, for spacecraft intercepts during midcourse guidance, followed by a ballistic coast to the endgame, is addressed. The problem is formulated in terms of relative motion in a general 3D framework. The proposed guidance law for the commanded thrust vector orientation consists of the sum of two terms: (1) along the line of sight unit direction and (2) along the zero effort miss component perpendicular to the line of sight and proportional to the miss itself and a guidance gain. If the guidance law is to be suitable for longer range targeting applications with significant ballistic coasting after burnout, determination of the zero effort miss must account for the different gravitational accelerations experienced by each vehicle. The proposed miss determination techniques employ approximations for the true differential gravity effect. Theoretical results are applied to a numerical engagement scenario and the resulting performance is evaluated in terms of the miss distances determined from nonlinear simulation.

Missing Children's Assistance Act. Hearings before the Subcommittee on Juvenile Justice of the Committee on the Judiciary. United States Senate. Ninety-Eighth Congress, Second Session on S. 2014, a Bill to Amend the Juvenile Justice and Delinquency Prevention Act of 1974 to Provide for Assistance in Locating Missing Children (February 7 and 21; March 8, 13, and 21, 1984).

ERIC Educational Resources Information Center

Congress of the U.S., Washington, DC. Senate Committee on the Judiciary.

This document presents testimony and proceedings from Congressional hearings on the problem of missing children and the remedies proposed by the Missing Children's Assistance Act. Opening testimony by Senators Arlen Specter and Paula Hawkins is presented, as is the text of the Missing Children's Assistance Act of 1983. Prepared testimony from…

Missing data frequency and correlates in two randomized surgical trials for urinary incontinence in women.

PubMed

Brubaker, Linda; Litman, Heather J; Kim, Hae-Young; Zimmern, Philippe; Dyer, Keisha; Kusek, John W; Richter, Holly E; Stoddard, Anne

2015-08-01

Missing data is frequently observed in clinical trials; high rates of missing data may jeopardize trial outcome validity. We determined the rates of missing data over time, by type of data collected and compared demographic and clinical factors associated with missing data among women who participated in two large randomized clinical trials of surgery for stress urinary incontinence, the Stress Incontinence Surgical Treatment Efficacy Trial (SISTEr) and the Trial of Midurethral Sling (TOMUS). The proportions of subjects who attended and missed each follow-up visit were calculated. The chi-squared test, Fisher's exact test and t test were used to compare women with and without missing data, as well as the completeness of the data for each component of the composite primary outcome. Data completeness for the primary outcome computation in the TOMUS trial (62.3%) was nearly double that in the SISTEr trial (35.7%). The follow-up visit attendance rate decreased over time. A higher proportion of subjects attended all follow-up visits in the TOMUS trial and overall there were fewer missing data for the period that included the primary outcome assessment at 12 months. The highest levels of complete data for the composite outcome variables were for the symptoms questionnaire (SISTEr 100 %, TOMUS 99.8%) and the urinary stress test (SISTEr 96.1%, TOMUS 96.7%). In both studies, the pad test was associated with the lowest levels of complete data (SISTEr 85.1%, TOMUS 88.3%) and approximately one in ten subjects had incomplete voiding diaries at the time of primary outcome assessment. Generally, in both studies, a higher proportion of younger subjects had missing data. This analysis lacked a patient perspective as to the reasons for missing data that could have provided additional information on subject burden, motivations for adherence and study design. In addition, we were unable to compare the effects of the different primary outcome assessment time-points in an identically designed trial. Missing visits and data increased with time. Questionnaire data and physical outcome data (urinary stress test) that could be assessed during a visit were least prone to missing data, whereas data for variables that required subject effort while away from the research team (pad test, voiding diary) were more likely to be missing. Older subjects were more likely to provide complete data.

On Obtaining Estimates of the Fraction of Missing Information from Full Information Maximum Likelihood

ERIC Educational Resources Information Center

Savalei, Victoria; Rhemtulla, Mijke

2012-01-01

Fraction of missing information [lambda][subscript j] is a useful measure of the impact of missing data on the quality of estimation of a particular parameter. This measure can be computed for all parameters in the model, and it communicates the relative loss of efficiency in the estimation of a particular parameter due to missing data. It has…

29 CFR Appendix B to Part 4050 - Examples of Benefit Payments for Missing Participants Under §§ 4050.8 Through 4050.10

Code of Federal Regulations, 2014 CFR

2014-07-01

... 29 Labor 9 2014-07-01 2014-07-01 false Examples of Benefit Payments for Missing Participants Under...) PENSION BENEFIT GUARANTY CORPORATION PLAN TERMINATIONS MISSING PARTICIPANTS Pt. 4050, App. B Appendix B to Part 4050—Examples of Benefit Payments for Missing Participants Under §§ 4050.8 Through 4050.10 The...

22 CFR 19.11-4 - Procedure in event a spouse or former spouse is missing.

Code of Federal Regulations, 2013 CFR

2013-04-01

... missing. 19.11-4 Section 19.11-4 Foreign Relations DEPARTMENT OF STATE PERSONNEL BENEFITS FOR SPOUSES AND... Procedure in event a spouse or former spouse is missing. If a participant or former participant has a spouse... affidavit with PER/ER/RET stating that his/her spouse or former spouse is missing and giving full name, last...

20 CFR 418.3640 - How do we determine if you had good cause for missing the deadline to request administrative review?

Code of Federal Regulations, 2013 CFR

2013-04-01

... missing the deadline to request administrative review? 418.3640 Section 418.3640 Employees' Benefits... Administrative Review Process § 418.3640 How do we determine if you had good cause for missing the deadline to... missing a deadline to request review we consider: (1) What circumstances kept you from making the request...