Author: Rafael Pilliard Hellwig
"Surveys are ubiquitous in the social sciences, and the best of them are meticulously planned out. Statisticians often decide on a sample size based on a theoretical design, and then proceed to inflate this number to account for “sample losses”. This ensures that the desired sample size is achieved, even in the presence of non-response…To simplify communication about non-response, a set of “outcome rates” have emerged over time…
outcomerate package calculates standard outcome rates in R in order to encourage transparent research, open methods, and scientific comparability. It does so using the American Association of Public Opinion Research ’s (AAPOR) definitions of the rates, which are the industry standard. By collecting them in one package, it saves you the time of repetitively looking up each rate and calculating them separately."
Read the full post here: https://ropensci.org/blog/2018/10/02/outcomerate/