At first, it seems obvious that the answer to this question is yes. After all, who wants a biased estimator? But … sometimes, the answer is no. Sometimes a biased estimator is better. Read more!

The full title of the book is *Multivariable model building: A pragmatic approach to regression analysis based on fractional polynomials for modelling continuous variables *. It’s a good book. It clearly presents its rationale for using a restricted set of fractional polynomials instead of either linear terms or splines. Read more!

In any form of regression model, we often think of the effects as *additive*. That is, we suppose that the effect of one variable can be added to the effect of another to get an accurate model. This is never strictly true, but how true is it? Is it true enough? How can we tell? Read more!

One question that sometimes arises in doing statistical analysis is whether to use a sophisticated method that is (in one way or another) more appropriate than a more typical method. The reason for its appropriateness might be that the usual method violates assumptions (e.g. we should use robust regression rather than OLS regression in some cases), answers the question better (e.g. we might use quantile regression instead of OLS regression in some cases), or is more efficient.

But the reviewers and editors at a journal may not know of the new method and may have issues with it. It might even lead to the paper being rejected.

What are your thoughts on this?

You’re about to do some research. You’ve got an idea in your field and you hope to turn it into a grant or an article or a dissertation. Right now, you may not know exactly how you want to work with the idea. It’s just a thought.

How can a statistician help you?

At this early stage, the consultant may be able to suggest novel ways of testing your idea, using analytic methods you’ve never heard of. Then, the statistical consultant will be able to help you plan a sample size and a sampling strategy, write up a methods section and start gathering and recording data in a sensible way.

After you gather data, your statistical consultant will be able to help you analyze the data and understand it, using methods that are appropriate rather than just some method you learned in your two statistics courses.

For instance, if you have a dependent variable and one or more independent variables you may want some sort of regression. But is it

But maybe you don’t need regression at all; or maybe you need a multilevel model. Perhaps factor analysis or principal component analysis or cluster analysis or multidimensional scaling will be vital to answering your research question.

Your statistical consultant will be able to help you figure it out.