Analysis of longitudinal data from animals with missing values using SPSS

Robust likelihood-based analysis of longitudinal data with missing values

Anova for Longitudinal Data with Missing Values

We carry out an ANOVA analysis to compare multiple treatment effects for longitudinal studies with missing values. The treatment effects are modeled semiparametrically via a partially linear regression which is flexible in quantifying the time effects of treatments. The empirical likelihood is employed to formulate nonparametric ANOVA tests for treatment effects with respect to covariates and t...

Analysis of longitudinal data with intermittent missing values using the stochastic EM algorithm

Longitudinal data are not uncommon in many disciplines where repeated measurements on a response variable are collected for all subjects. Some intended measurements may not be available for some subjects resulting in a missing data pattern. Dropout pattern occurs when some subjects leave the study prematurely. The missing data pattern is defined as intermittent if a missing value followed by an...

Estimating treatment effects from longitudinal clinical trial data with missing values: comparative analyses using different methods.

The selection of a method for estimating treatment effects in an intent-to-treat analysis from clinical trial data with missing values often depends on the field of practice. The last observation carried forward (LOCF) analysis assumes that the responses do not change after dropout. Such an assumption is often unrealistic. Analysis with completers only requires that missing values occur complet...

analysis of longitudinal binary outcomes in clinical trials with low percentage of missing values

in interventional or observational longitudinal studies, the issue of missing values is one of the main concepts that should be investigated. the researcher's main concerns are the impact of missing data on the final results of the study and the appropriate methods that missing values should be handled. regarding the role and the scale of the variable that missing values have been occurred and ...