inst/doc/panel-comparisons.R

In wavecov: Overlap-Aware Workforce Wave Comparisons

## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

## ----setup--------------------------------------------------------------------
library(wavecov)

## -----------------------------------------------------------------------------
set.seed(123)

n_id   <- 100
waves  <- 0:2
ids    <- sprintf("ee%03d", 1:n_id)

base_panel <- expand.grid(
  eeid  = ids,
  wave  = waves,
  KEEP.OUT.ATTRS = FALSE,
  stringsAsFactors = FALSE
)

# Simple group assignment (one group per id-wave, then reused)
base_panel$group <- sample(c("Group A", "Group B"),
                           nrow(base_panel), replace = TRUE)

# Engagement metric block
eng_panel <- base_panel
eng_panel$metric_id <- "engagement_score"
eng_panel$metric <-
  3.5 +
  0.2 * eng_panel$wave +
  ifelse(eng_panel$group == "Group A", 0.1, -0.1) +
  rnorm(nrow(eng_panel), sd = 0.4)

# Pay index metric block
pay_panel <- base_panel
pay_panel$metric_id <- "pay_index"
pay_panel$metric <-
  1.0 +
  0.05 * pay_panel$wave +
  ifelse(pay_panel$group == "Group A", 0.05, -0.05) +
  rnorm(nrow(pay_panel), sd = 0.1)

# Stack into one long panel
panel <- rbind(eng_panel, pay_panel)

head(panel)
nrow(panel)  # should be 100 ids * 3 waves * 2 metrics = 600

## -----------------------------------------------------------------------------
wave_pairs <- data.frame(
  wave_0 = c(0, 1),
  wave_1 = c(1, 2)
)

wave_pairs

## -----------------------------------------------------------------------------
batch_res <- compare_waves_batch(
  data          = panel,
  wave_pairs    = wave_pairs,
  id_col        = "eeid",
  wave_col      = "wave",
  metric_col    = "metric",
  metric_id_col = "metric_id",
  group_cols    = "group",
  method        = "auto",
  reliability   = 0.8
)

head(batch_res)

## -----------------------------------------------------------------------------
batch_res_min <- batch_res[, c(
  "wave_0", "wave_1",
  "metric_id", "group",
  "estimate", "se",
  "ci_lower", "ci_upper",
  "method"
)]

head(batch_res_min)

## -----------------------------------------------------------------------------
eng_changes <- subset(batch_res_min, metric_id == "engagement_score")
eng_changes 

## -----------------------------------------------------------------------------
subset(batch_res_min,        metric_id == "engagement_score" &        wave_0 == 0 & wave_1 == 1)