What makes repeated measures data unique from other data?

What makes repeated measures data unique from other data?

The covariance structure of the observed data is what makes repeated measures data unique-the data from the same subject may be correlated and the correlation should be modeled if it exists. GEE can take into account the correlation of within-subject data (longitudinal studies) and other studies in which data are clustered within subgroups.

What does Gee for repeated measures analysis do?

GEE can take into account the correlation of within-subject data (longitudinal studies) and other studies in which data are clustered within subgroups. Failure to take into account correlation would lead to the regression estimates (Bs) being less efficient- meaning they would be more widely scattered around the true population value.

Is there a diet by time interaction in repeated measures?

Time is the within-subject factor. In this study we would be interested in how the weight and diet changes over time, i.e. is there a diet by time interaction? The covariance structure of the observed data is what makes repeated measures data unique-the data from the same subject may be correlated and the correlation should be modeled if it exists.

What kind of data is used to predict clinical outcome?

The primary data consists of a binary independent variable (patient test – positive or negative; there are some missing values which are being excluded for now) for which we want to determine if it is predictive for a given clinical outcome.

Which is the best structure for repeated measures?

The two most promising structures are Autoregressive Heterogeneous Variances and Unstructured since these two models have the smallest AIC values and the -2 Log Likelihood scores are significantly smaller than the -2 Log Likehood scores of other models.

How is the univariate test used in repeated measures?

The univariate tests assumes that the variance-covariance structure has compound symmetry. There is a single Variance (represented by s2) for all 3 of the time points and there is a single covariance (represented by s1) for each of the pairs of trials.

How are diets used in repeated measures analysis?

Observations from an individual tend to be correlated and the correlation must be taken into account for valid inference. Three different types of diets are randomly assigned to a group of men. Each man is assigned a different diet and the men are weighed weekly for one year. The treatment is diet type and is the between-subjects factor.

How are regression coefficients used in probit link?

Regression coefficients are the expected change in the log of the mean of the dependent variable for each change in a covariate Also probit link for cumulative predictive analysis of binary or ordered dependent variables and cumulative logit for ordered multinominal data

How can you account for the repeated measurements?

You can account for the repeated measurements by doing one of two things, which each have slightly different interpretations: