Biostatistics- Regression

Review Of Regressions: Simple, Multiple, Logistic

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Side ASide B
tests the null hypotheis that slope = 0.HO: slope (b)= 0
simple linear regression
assumptions for hypothesis testing in regression analysis
RESIDUALS must be1.uncorrelated with one another2. normally distributed3. equal standard deviations
allows you to evaluate the joint and the independent effects of each of several predictor (indepenent) variables
multiple linear regression
tests the HO: bi =0
multiple linear regression
outcomes are continuous
simple and multiple regressoin
outcome measures is dichoomous
logistic regression
pros of simple linear regression
if r2 high then beta is...
cons of multiple linear regression
no r2
pros of logistic regression
covariate analysis
assumptions of logistic regression
independece between subjects

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