Splines, including polynomials, are traditionally used to model nonlinear relationships involving continuous predictors. However, when they are included in linear models (or generalized linear models), the estimated parameters for polynomials are not easy for nonmathematicians to understand, and...

Applied scientists, especially public health scientists, frequently want to know how much good can be caused by a proposed intervention. For instance, they might want to estimate how much we could decrease the level of a disease, in a dream scenario where the whole world stopped smoking,...

Factor variables are defined as categorical variables with integer values, which may represent values of some other kind, specified by a value label. We frequently want to generate such variables in Stata datasets, especially resultssets, which are output Stata datasets produced by Stata...

So-called non-parametric methods are in fact based on estimating and testing parameters, usually either rank parameters or spline parameters. Two comprehensive packages for estimating these are somersd (for rank parameters) and bspline (for spline parameters). Both of these estimate a wide range...

The parmest package is used with Stata estimation commands to produce output datasets (or results-sets) with one observation per estimated parameter, and data on parameter names, estimates, confidence limits, p-values, and other parameter attributes. These results-sets can then be input to other...

Insufficient confounder adjustment is viewed as a common source of "false discoveries", especially in the epidemiology sector. However, adjustment for "confounders" that are correlated with the exposure, but which do not independently predict the outcome, may cause loss of power to detect the...

The parmest package creates output datasets (or results sets) with one observation for each of a set of estimated parameters, and data on the parameter estimates, standard errors, degrees of freedom, t or z statistics, p-values, confidence limits, and other parameter attributes specified by the...

The cendif module is part of the somersd package, and calculates confidence intervals for the Hodges–Lehmann median difference between values of a variable in two subpopulations. The traditional Lehmann formula, unlike the formula used by cendif, assumes that the two subpopulation...