I'd like to ask you something about the bootstrap method. If I understood correctly, I can use this method when the size of a sample is small, in order to extract more information. For example, applying a Cox model I noticed that when I had a bigger sample (n=1050), I found several significant small effects and a big significant effect for only one variable. When I reduced the sample size (n=300), all small effects disappeared, remaining only the variable with big effect as significant variable. Can I use a bootstrap method on this sample (n=321) and realize many Cox models (for example generating 1000 samples) in order to make stronger the effects of the variables with small effects?
Thank you for your attention.