Results 201 to 210 of about 37,466 (251)

Regression Models for the Analysis of Pretest/Posttest Data

Biometrics, 1997
Summary: The standard repeated measures ANOVA and ANCOVA models for data from pretest/posttest experiments may not be completely adequate either when a null pretest measurement implies that the posttest measurement is also null or when the data are heteroscedastic.
Singer, Julio M., Andrade, Dalton F.
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Regression models for pretest/posttest data in blocks

Statistical Modelling, 2004
We consider regression models with no intercepts to analyse pretest/posttest data from a dental study conducted under an experimental design involving a blocked factorial structure with two within individual factors. The proposed models accommodate block effects, heteroscedasticity, nonlinear relations between pretest and posttest measures and ...
Julio Singer, Juvencio Nobre
exaly   +3 more sources

Semiparametric Estimation of Treatment Effect in a Pretest‐Posttest Study

Biometrics, 2003
Summary.  Inference on treatment effects in a pretest‐posttest study is a routine objective in medicine, public health, and other fields. A number of approaches have been advocated. We take a semiparametric perspective, making no assumptions about the distributions of baseline and posttest responses.
Leon, Selene, Tsiatis, Anastasios A., Davidian, Marie   +2 more
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Choosing a Pretest-Posttest Analysis

The American Statistician, 1988
Abstract Pretest-posttest designs serve as building blocks for other more complicated repeated-measures designs. In settings where subjects are independent and errors follow a bivariate normal distribution, data analysis may consist of a univariate repeated-measures analysis or an analysis of covariance.
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Pretest-Posttest Change

2019
Pretest-posttest change can be studied at the population level and at the individual level. Within-group change is the change of a population parameter, for example, the mean from pretest to posttest. Between-groups change is the difference of within-group change between (e.g., E- and C-) groups.
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Analysis of the Pretest–Posttest Designs

Journal of the American Statistical Association, 2002
(2002). Analysis of the Pretest–Posttest Designs. Journal of the American Statistical Association: Vol. 97, No. 458, pp. 654-655.
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Missing Data in Randomized Pretest Posttest Studies

Multivariate Behavioral Research, 2018
Researchers have been given little guidance on handling missing posttest data when assessing the average treatment effect (ATE) in randomized pretest posttest (“RPP”) designs.
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EVALUATING PRETEST-POSTTEST CONTROL GROUP EXPERIMENTS

Perceptual and Motor Skills, 1992
The analysis of pretest-posttest control group experiments was simulated using gain scores, analysis of covariance, and posttest only methods. In addition, a sequential procedure was evaluated in which gain scores were used unless the initial difference between the groups on the pretest was large at which time a covariance was used.
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An imputation based empirical likelihood approach to pretest–posttest studies

Canadian Journal of Statistics, 2015
AbstractPretest–posttest studies are an important and popular method for assessing treatment effects or the effectiveness of an intervention in many areas of scientific research. There are two distinct features for this type of study: availability of baseline information for all subjects in the study and missingness by design of measures of the ...
Chen, Min, Wu, Changbao, Thompson, Mary E.   +2 more
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Efficiency Study of Estimators for a Treatment Effect in a Pretest–Posttest Trial

The American Statistician, 2001
Several possible methods used to evaluate treatment effects in a randomized pretest–posttest trial with two treatment groups are the two-sample t test, the paired t test, analysis of covariance I (ANCOVA I), the analysis of covariance II (ANCOVA II), and generalized estimating equations (GEE).
Yang L., Tsiatis A. A.
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