<p>All models had the same random effects structure (ID and year as random intercepts) and were fitted with ML estimation. The full model (Model 3) included the following variables as fixed effects: SIC, SIC<sup>2</sup>, sex, Mark, TSM, BERG, Day, BERG : SIC, BERG : SIC<sup>2</sup>. The fit of each successively less complex model was assessed using likelihood ratio tests. LR refers to log-likelihood ratio test statistics.</p
<p>The results for model A (A) and for model B (B) are shown. The residuals of model A show a clear ...
<p>Estimated log likelihood, fit statistics, selected summary measures, and a likelihood ratio test ...
<p>Statistically significant variables in the backward logistic regression model based on likelihood...
<p>All models had the same fixed effects structure and were fitted with REML estimation. The fit of ...
<p>*df = degrees freedom, ΔAIC = change in AIC associated with removal of each model term, LRT (χ<su...
University of Minnesota Ph.D. disseration. June 2010. Major: Educational Psychology. Advisor: Jeffre...
Linear mixed effect (LME) models have become popular in modeling data in a wide variety of fields, p...
<p>Reference models are indicated in bold. To test the effect of treatment, the reference model was ...
<p><sup>a</sup>aOR: adjusted odds ratio.</p><p><sup>b</sup> CI: confidence interval.</p><p>The best ...
<p>Number of observations: 178. Number of groups (random effect species): 5. AIC = 1331.97, BIC = 13...
Statistical models are simple mathematical rules derived from empirical data describing the associat...
<p>Note: Random effect for subject intercept had SD of 12.49. SE: standard error of mean; df: degree...
Logistic regression model of the impact of setting, prevention level, and study design on the odds t...
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAM...
Mixed-effect modeling is recommended for data with repeated measures, as often encountered in design...
<p>The results for model A (A) and for model B (B) are shown. The residuals of model A show a clear ...
<p>Estimated log likelihood, fit statistics, selected summary measures, and a likelihood ratio test ...
<p>Statistically significant variables in the backward logistic regression model based on likelihood...
<p>All models had the same fixed effects structure and were fitted with REML estimation. The fit of ...
<p>*df = degrees freedom, ΔAIC = change in AIC associated with removal of each model term, LRT (χ<su...
University of Minnesota Ph.D. disseration. June 2010. Major: Educational Psychology. Advisor: Jeffre...
Linear mixed effect (LME) models have become popular in modeling data in a wide variety of fields, p...
<p>Reference models are indicated in bold. To test the effect of treatment, the reference model was ...
<p><sup>a</sup>aOR: adjusted odds ratio.</p><p><sup>b</sup> CI: confidence interval.</p><p>The best ...
<p>Number of observations: 178. Number of groups (random effect species): 5. AIC = 1331.97, BIC = 13...
Statistical models are simple mathematical rules derived from empirical data describing the associat...
<p>Note: Random effect for subject intercept had SD of 12.49. SE: standard error of mean; df: degree...
Logistic regression model of the impact of setting, prevention level, and study design on the odds t...
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAM...
Mixed-effect modeling is recommended for data with repeated measures, as often encountered in design...
<p>The results for model A (A) and for model B (B) are shown. The residuals of model A show a clear ...
<p>Estimated log likelihood, fit statistics, selected summary measures, and a likelihood ratio test ...
<p>Statistically significant variables in the backward logistic regression model based on likelihood...