I am conducting analysis on my honors thesis. I have one binary outcome variable, having high or low intimate relationship quality. I want to use logistic regression to predict the odds of having high or low intimate relationship quality. I have 5 predictor variables: depression, anxiety, illness acceptance, self-concept and physical self-concept. I have been advised not to conduct one multiple logistic regression with all the predictors included, but instead conduct 5 simple logistic regressions for each individual predictor separately. Is this an appropriate approach or should I conduct a multiple logistic regression with all 5 predictors in the one model?
Advised by my supervisor, they said that was how I should conduct the analysis but didn't give many reasons. My sample size is 115 with 33 in low intimate relationship quality and 82 in high intimate relationship quality. Data was collected via online surveys. Basically, I am unsure if conducting 5 separate analyses is the best way to conduct my analysis, it seems that when I do 5 separate logistic regressions all predictors are significant, but if I conduct one multiple logistic regression with all predictors, only one predictor is significant.