Add to ORKGIn medical research, data sets are seldom complete. That is, some of the values that should have been recorded, are missing for some of the persons in the study. Traditionally, “complete case ” analysis has been used in such situations. That is, only cases (persons) with complete data are included in the analysis. In addition reducing the sample size, this method typically gives biased results. Better methods include multiple imputation (MI), full maximum likelihood (ML), mixed models, and generalized estimating equations (GEE). The candidate shall give a short description of alternative methods for handling missing values. The main part of the thesis consists of analyses of longitudinal data from
Many researchers face the problem of missing data in longitudinal research. Especially, high risk sa...
Mediante este trabajo se pretende caracterizar los estudios con datos longitudinales y los problemas...
Biomedical research is plagued with problems of missing data, especially in clinical trials of medic...
Missing data is a concept used to describe the values that are, for some reason, not observed in dat...
Using standard missing data taxonomy, due to Rubin and co-workers, and simple algebraic derivations,...
Using standard missing data taxonomy, due to Rubin and co-workers, and simple algebraic derivations,...
Using standard missing data taxonomy, due to Rubin and co-workers, and simple algebraic derivations,...
Using standard missing data taxonomy, due to Rubin and co-workers, and simple algebraic derivations,...
n Abstract Missing data are a pervasive problem in many public health investiga-tions. The standard ...
Missing responses are very common in longitudinal data. Much research has been going on, on ways to ...
Missing data are a potential source of bias in the results of randomised controlled trials (RCTs), b...
Missing data are a potential source of bias in the results of randomised controlled trials (RCTs), b...
n Abstract Missing data are a pervasive problem in many public health investiga-tions. The standard ...
Many researchers face the problem of missing data in longitudinal research. Especially, high risk sa...
Missing values are ubiquitous in clinical research. Especially in case of a longitudinal study, the ...
Many researchers face the problem of missing data in longitudinal research. Especially, high risk sa...
Mediante este trabajo se pretende caracterizar los estudios con datos longitudinales y los problemas...
Biomedical research is plagued with problems of missing data, especially in clinical trials of medic...
Missing data is a concept used to describe the values that are, for some reason, not observed in dat...
Using standard missing data taxonomy, due to Rubin and co-workers, and simple algebraic derivations,...
Using standard missing data taxonomy, due to Rubin and co-workers, and simple algebraic derivations,...
Using standard missing data taxonomy, due to Rubin and co-workers, and simple algebraic derivations,...
Using standard missing data taxonomy, due to Rubin and co-workers, and simple algebraic derivations,...
n Abstract Missing data are a pervasive problem in many public health investiga-tions. The standard ...
Missing responses are very common in longitudinal data. Much research has been going on, on ways to ...
Missing data are a potential source of bias in the results of randomised controlled trials (RCTs), b...
Missing data are a potential source of bias in the results of randomised controlled trials (RCTs), b...
n Abstract Missing data are a pervasive problem in many public health investiga-tions. The standard ...
Many researchers face the problem of missing data in longitudinal research. Especially, high risk sa...
Missing values are ubiquitous in clinical research. Especially in case of a longitudinal study, the ...
Many researchers face the problem of missing data in longitudinal research. Especially, high risk sa...
Mediante este trabajo se pretende caracterizar los estudios con datos longitudinales y los problemas...
Biomedical research is plagued with problems of missing data, especially in clinical trials of medic...