Sentence examples for multivariate fixed effects from inspiring English sources

We used multivariate fixed effects models for longitudinal data to examine the GRP-RTF and the GRP-CFR relationships excluding regions with extreme values.

Measures of effect were assessed using multivariate fixed effects logistic regression model accounting for clustering at facility level and the results are presented as adjusted odds ratios.

Measures of effect were assessed using multivariate fixed effects logistic regression model accounting for clustering at facility level and the results were presented as adjusted odds ratios or incidence rate ratios (IRR).

In the multivariate model, the fixed effects were modeled to have separate effects on each response variable.

Random = random effects model; Fixed = fixed effects model.

This study uses three complementary methods: trends analysis, decomposition and longitudinal multivariate models (fixed effect regression models).

As further analysis with the same database, we conducted a propensity score matching analysis and fixed effects, multivariate regressions with propensity score weighting.

Variation in long-term sickness absence was explained through a fixed effects multivariate regression analysis, with years since merger as the independent variable.

Variation in long-term sickness absence was explained through a fixed effects multivariate regression analysis using panel data with years-since-merger as the independent variable.

In addition to the random-effects models, we estimated an overall multivariate model with country fixed effects and found the following variables to be positively associated with depressive symptoms: chronic disease, lower SES, female, and living in a non-multigenerational household (Additional file 1: Table S2).

Using data from a nationally representative sample of adolescents we utilize a multivariate structural model with school-level fixed effects to account for the problems of contextual effects, correlated effects and peer selections to purge the potential biases from the estimates of peer influence.