1999
DOI: 10.1111/j.0006-341x.1999.00652.x
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Predictive Margins with Survey Data

Abstract: In the analysis of covariance, the display of adjusted treatment means allows one to compare mean (treatment) group outcomes controlling for different covariate distributions in the groups. Predictive margins are a generalization of adjusted treatment means to nonlinear models. The predictive margin for group r represents the average predicted response if everyone in the sample had been in group r. This paper discusses the use of predictive margins with complex survey data, where an important consideration is … Show more

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Cited by 782 publications
(564 citation statements)
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References 13 publications
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“…We used logistic regression to estimate relative risks from abuse for BMI 30 and 40. Because odds ratios from logistic regression may overestimate relative risks, we used predictive margins 16 to estimate relative risks from predicted values produced by logistic regression. Standard normal confidence intervals for logrelative risks were calculated using bootstrap methods with 200 replications, 17 then transformed back to the original relative risk scale.…”
Section: Discussionmentioning
confidence: 99%
“…We used logistic regression to estimate relative risks from abuse for BMI 30 and 40. Because odds ratios from logistic regression may overestimate relative risks, we used predictive margins 16 to estimate relative risks from predicted values produced by logistic regression. Standard normal confidence intervals for logrelative risks were calculated using bootstrap methods with 200 replications, 17 then transformed back to the original relative risk scale.…”
Section: Discussionmentioning
confidence: 99%
“…Slightly more than half of television beer ads appear on sports programming37 , 38 . Of these, a substantial portion appears on ESPN (Nielsen Media Research), a cable network.…”
Section: Methodsmentioning
confidence: 99%
“…The regressions followed the generalized linear model with log link and gamma distribution, and adjusted for patient characteristics, including demographics (age, sex, and region of residence), CCI, and subtypes of SLE (discoid/ cutaneous lupus and lupus nephritis), during the study period. Based on regression results, the incremental total costs were estimated for each of the GC cohorts, relative to no GC use, such that the expected instantaneous change in costs was a function of a change in GC variables while keeping all other covariates constant (21). Analyses were performed using SAS, version 9.2.…”
Section: Significance and Innovationsmentioning
confidence: 99%