emacalc-package: emacalc: A package for performing useful calculations in...

Description Person aggregates Day aggregates SD Day functions Rel SD Day functions Lagging functions Splitting functions Utilities Trimming functions Author(s)

Description

The emacalc package was built to make it easier to work with experience sampling data. It contains functions to easily calculate person-level and day-level variables, lag variables at different levels, split data into person and moment level dataframes, and numerous other utility functions.

Person aggregates

Calculate aggregate statistics at the person level

Person aggregation functions:

person_mean, person_min, person_max, person_sd, person_relsd

Day aggregates

Calculate aggregate statistics at the day level

day_mean, day_min, day_max, day_sd, day_relsd

SD Day functions

Calculate standard deviation of day level statistics

day_mean_sd, day_min_sd,day_max_sd

Rel SD Day functions

Calculate relative standard deviation of day level statistics:

day_mean_relsd, day_min_relsd,day_max_relsd

Lagging functions

Lag variables at appropriate levels:

esm_lag, esm_day_lag

Splitting functions

Split up complete datasets into subsets of data with only higher (e.g. trait) or lower (e.g. moment) level variables

keep_bottom, keep_top

Utilities

Tools for managing operations on many variables

operate_cols, rename_cols, rescale_cols, reverse_cols, center_cols

Trimming functions

tools to trim datasets to only groups with enough valid observations

trim_min_obs trim_min_valid_obs

Author(s)

Sean C Murphy, seanchrismurphy@gmail.com


seanchrismurphy/emacalc documentation built on May 12, 2019, 2:03 p.m.