quest: Pre-processing Questionnaire Data
In quest: Prepare Questionnaire Data for Analysis

Description Types of functions Abbreviations

quest is a package for pre-processing questionnaire data to get it ready for statistical modeling. It contains functions for investigating missing data (e.g., rowNA), reshaping data (e.g., wide2long), validating responses (e.g., revalids), recoding variables (e.g., recodes), scoring (e.g., scores), centering (e.g., centers), aggregating (e.g., aggs), shifting (e.g., shifts), etc. Functions whose first phrases end with an s are vectorized versions of their functions without an s at the end of the first phrase. For example, center inputs a (atomic) vector and outputs a atomic vector to center and/or scale a single variable; centers inputs a data.frame and outputs a data.frame to center and/or scale multiple variables. Functions that end in _by are calculated by group. For example, center does grand-mean centering while center_by does group-mean centering. Putting the two together, centers_by inputs a data.frame and outputs a data.frame to center and/or scale multiple variables by group. Functions that end in _if are calculated dependent on the frequency of observed values (aka amount of missing data). The quest package uses the str2str package internally to convert R objects from one structure to another. See str2str for details.

There are two main types of functions. 1) Helper functions that primarily exist to save a few lines of code and are primarily for convenience (e.g., vecNA). 2) Functions for wrangling questionnaire data (e.g., nom2dum, reverses).

See the table below