Bøger udgivet af Stata Press

Bayesian Analysis with Stata is written for anyone interested in applying Bayesian methods to real data easily. The book shows how modern analyses based on Markov chain Monte Carlo (MCMC) methods are implemented in Stata both directly and by passing Stata datasets to OpenBUGS or WinBUGS for computation, allowing Statäs data management and graphing capability to be used with OpenBUGS/WinBUGS speed and reliability. The book emphasizes practical data analysis from the Bayesian perspective and covers the selection of realistic priors, computational efficiency and speed, the assessment of convergence, the evaluation of models, and the presentation of results.

Speaking Stata Graphics is ideal for researchers who want to produce effective, publication-quality graphs. A compilation of articles from the popular Speaking Stata column by Nicholas J. Cox, this book provides valuable insights about Stata's built-in and user-written statistical-graphics commands.

Through real-world case studies, this book shows how to use Stata to estimate a class of flexible parametric survival models. It discusses the modeling of time-dependent and continuous covariates and looks at how relative survival can be used to measure mortality associated with a particular disease when the cause of death has not been recorded. The book describes simple quantification of differences between any two covariate patterns through calculation of time-dependent hazard ratios, hazard differences, and survival differences.

Suitable for data analysts, this book demonstrates how to design and implement efficient workflows for both one-person projects and team projects. It describes planning, organizing, and documenting your work. It then introduces how to write and debug Stata do-files and how to use local and global macros.

This practical guide explores all the features of Statäs sem command. This revised edition includes output, syntax, and instructions for fitting models with the Stata 13 SEM Builder. It shows how this graphical interface allows users to draw publication-quality path diagrams and fit the models without writing any programming code. Each model is presented along with the necessary Stata code. The datasets used are available for download online.