Analysis of large-scale assessment in education (LSAE) datasets is challenging for many researchers because of the need to use specific statistical methods that properly account for complex sampling designs and multiple latent variable indicators, called plausible values (PVs). In this chapter, we discuss resampling methods that allow for the proper estimation of sampling variance and PVs methodology that allows for inferring the latent variables, in a short and accessible way. We show how to properly utilize those methods in the context of LSAEs presenting examples of typical LSAEs analyses. The examples show how to perform analyses in a convenient way using additional packages that are available for two popular statistical software programs: Stata and R. We present pisatools, piaactools, and repest packages from Stata and mitools, survey, and svyPVpm libraries from R. For both environments, analyses involving descriptive statistics, frequency tables, OLS regression, and logistic regression are presented.