A comparison of inclusive and restrictive strategies in modern missing data procedures.

Collins, Linda M.; Schafer, Joseph L.; Kam, Chi Ming

doi:10.1037/1082-989x.6.4.330

Cited by 1,972 publications

(1,666 citation statements)

References 18 publications

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“…We have not reported results obtained by analysing only the complete cases because of the potential bias and loss of precision associated with the large proportion of missing income data; instead, we used multiple imputation. We imputed all missing data under a missing at random (MAR) assumption and adopted an inclusive strategy for the imputation model (31)(32)(33) .…”

Section: Discussionmentioning

confidence: 99%

A multilevel study of area socio-economic status and food purchasing behaviour

Turrell

Bentley

Thomas

et al. 2009

Public Health Nutr.

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Objective: The present study examined the association between area socioeconomic status (SES) and food purchasing behaviour. Design: Data were collected by mail survey (64?2 % response rate). Area SES was indicated by the proportion of households in each area earning less than $AUS 400 per week, and individual-level socio-economic position was measured using education, occupation and household income. Food purchasing was measured on the basis of compliance with dietary guideline recommendations (for grocery foods) and variety of fruit and vegetable purchase. Multilevel regression analysis examined the association between area SES and food purchase after adjustment for individual-level demographic (age, sex, household composition) and socioeconomic factors. Setting: Melbourne city, Australia, 2003. Subjects: Residents of 2564 households located in fifty small areas. Results: Residents of low-SES areas were significantly less likely than their counterparts in advantaged areas to purchase grocery foods that were high in fibre and low in fat, salt and sugar; and they purchased a smaller variety of fruits. There was no evidence of an association between area SES and vegetable variety. Conclusions: In Melbourne, area SES was associated with some food purchasing behaviours independent of individual-level factors, suggesting that areas in this city may be differentiated on the basis of food availability, accessibility and affordability, making the purchase of some types of foods more difficult in disadvantaged areas.

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Section: Discussionmentioning

confidence: 99%

A multilevel study of area socio-economic status and food purchasing behaviour

Turrell

Bentley

Thomas

et al. 2009

Public Health Nutr.

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“…In other words, as long as the missing values of y on occasion i are not unique predictors of missingness for y on occasion i after controlling for observed values of y from previous time points or other predictors in the model (e.g., other within-subjects or between-subjects covariates), then the missingness is ignorable under maximum likelihood estimation, which will yield unbiased parameter estimates and standard errors (Schafer & Graham, 2002). Moreover, Collins, Schafer, and Kam (2001) recently demonstrated that in a variety of realistic missingness scenarios, the persistence of a unique relationship between scores on y and missingness on y can have a rather minor impact on parameter estimates and their standard errors. 3 We controlled for initial status and linear change in these models and equivalent models in Studies 2 and 3 because multivariate models that we ran with these data (Raudenbush, Brennan, & Barnett, 1995) within-person equations for evaluating simultaneously the association of anger or fear (the presumed mediators) and rumination (the predictor variable) with the TRIM variables (the outcomes) were of the form: (6) and we again included between-persons equations as in Equations 3-5 above.…”

Section: Statistical Models and Analysesmentioning

confidence: 99%

Rumination, emotion, and forgiveness: Three longitudinal studies.

McCullough¹,

Bono²,

Root³

2007

Journal of Personality and Social Psychology

272

185

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In 3 studies, the authors investigated whether within-persons increases in rumination about an interpersonal transgression were associated with within-persons reductions in forgiveness. Results supported this hypothesis. The association of transient increases in rumination with transient reductions in forgiveness appeared to be mediated by anger, but not fear, toward the transgressor. The association of rumination and forgiveness was not confounded by daily fluctuations in positive affect and negative affect, and it was not moderated by trait levels of positive affectivity, negative affectivity, or perceived hurtfulness of the transgression. Cross-lagged associations of rumination and forgiveness in Study 3 more consistently supported the proposition that increased rumination precedes reductions in forgiveness than the proposition that increased forgiveness precedes reductions in rumination.

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“…Specifically, all variables for the analysis model, including the outcome variable (Moons et al, 2006;StataCorp, 2013) should be included. A comparison of a "restrictive" (limited use of auxiliary) variables, and an "inclusive" (including many auxiliary variables) strategies clearly found the latter to be superior (Collins et al, 2001).…”

Section: Variables Used In Imputationmentioning

confidence: 98%

“…The benefits of MI in the face of NMAR data are not as predictable. However, it has been reported that MI is robust to the NMAR mechanism if the % of missing observations is <25% and the correlation between the cause of missingness and the variable subject to missingness was <.4 (Collins et al, 2001). …”

Section: Simulation Study -Based On Observed Missing Data Patternmentioning

confidence: 99%

Multiple imputation in veterinary epidemiological studies: a case study and simulation

Dohoo

Nielsen

Emanuelson

2016

Preventive Veterinary Medicine

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The problem of missing data occurs frequently in veterinary epidemiological studies. Most studies use a complete case (CC) analysis which excludes all observations for which any relevant variable have missing values. Alternative approaches (most notably multiple imputation (MI)) which avoid the exclusion of observations with missing values are now widely available but have been used very little in veterinary epidemiology.This paper uses a case study based on research into dairy producers' attitudes toward mastitis control procedures, combined with two simulation studies to evaluate the use of MI and compare results with a CC analysis. MI analysis of the original data produced results which had relatively minor differences from the CC analysis. However, most of the missing data in the original data set were in the dependent variable and a subsequent simulation study based on the observed missing data pattern and 1000 simulations showed that an MI analysis would not be expected to offer any advantages over a CC analysis in this situation. This was true regardless of the missing data mechanism (MCAR -missing completely at random, MARmissing at random, or NMAR -not missing at random) underlying the missing values. Surprisingly, recent textbooks dealing with MI make little reference to this limitation of MI for dealing with missing values in the dependent variable.An additional simulation study (1000 runs for each of the three missing data mechanisms) compared MI and CC analyses for data in which varying levels (n=7) of missing data were created in predictor variables. This study showed that MI analyses generally produced results that were less biased on average, were more precise (smaller SEs), were more consistent (less variability between simulation runs) and consequently were more likely to produce estimates that were close to the "truth" (results obtained from a data set with no missing values). While 3 the benefit of MI varied with the mechanism used to generate the missing data, MI always performed as well as, or better than, CC analysis.

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A comparison of inclusive and restrictive strategies in modern missing data procedures.

Cited by 1,972 publications

References 18 publications

A multilevel study of area socio-economic status and food purchasing behaviour

A multilevel study of area socio-economic status and food purchasing behaviour

Rumination, emotion, and forgiveness: Three longitudinal studies.

Multiple imputation in veterinary epidemiological studies: a case study and simulation

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