Estimate anchor reliability using CFA

tr_reliability() estimates the reliability of an anchor or transition rating item using confirmatory factor analysis. The reliability estimate is the R-squared value of the anchor item from the fitted CFA model.

Usage

tr_reliability(
  data,
  model = NULL,
  anchor = NULL,
  xsec = FALSE,
  pair_by = c("position", "suffix"),
  t1_suffix = NULL,
  t2_suffix = NULL,
  factor_names = NULL,
  item_type = NULL,
  continuous_items = NULL,
  modification = TRUE,
  mi_cut = 0.3,
  complete_cases = TRUE,
  print_model = TRUE,
  verbose = TRUE,
  ...
)

Arguments

data: A data frame containing items and an anchor variable.
model: Optional lavaan model syntax. If NULL, syntax is generated automatically using tr_reliability_model().
anchor: Character. Name of the anchor variable. If NULL, the final column of data is treated as the anchor.
xsec: Logical. If TRUE, estimate cross-sectional anchor reliability. If FALSE, estimate longitudinal anchor / transition-rating reliability.
pair_by: Pairing method for longitudinal data. "position" assumes Time 1 items followed by Time 2 items. "suffix" detects pairs using t1_suffix and t2_suffix.
t1_suffix: Regex suffix identifying Time 1 items when pair_by = "suffix".
t2_suffix: Regex suffix identifying Time 2 items when pair_by = "suffix".
factor_names: Optional character vector of factor name(s). If NULL, defaults to "F1" when xsec = TRUE, and c("F1", "F2") when xsec = FALSE.
item_type: Optional character. Type of items used as indicators. If NULL, defaults to "ordinal" unless continuous_items is supplied, in which case it defaults to "mixed". "ordinal" treats all items and the anchor as ordered categorical variables. "continuous" treats all items as continuous while still treating the anchor as ordered. "mixed" treats all items as ordered except those listed in continuous_items; the anchor is always treated as ordered.
continuous_items: Optional character vector of item names to treat as continuous. If supplied and item_type = NULL, item_type is automatically set to "mixed". Do not include the anchor variable; it is always treated as ordered.
modification: Logical. If TRUE, return modification indices with sepc.lv > mi_cut.
mi_cut: Numeric. Cutoff for standardized latent-variable modification indices.
complete_cases: Logical. If TRUE, retain only complete cases before fitting the model.
print_model: Logical. If TRUE, print the generated lavaan syntax.
verbose: Logical. If TRUE, print progress messages.
...: Additional arguments passed to lavaan::cfa().

Value

An object of class tr_reliability.

Details

This function follows the CFA approach for estimating transition-rating reliability described by Griffiths et al. (2022). For longitudinal data, Time 1 items load on the first factor, Time 2 items load on the second factor, and the anchor loads on both factors. Residuals of corresponding items across time-points are allowed to correlate. No constraints are placed on loadings or thresholds.

For cross-sectional data, a one-factor CFA model is used, with the anchor item included as an indicator of the latent factor.

References

Griffiths P, Terluin B, Trigg A, Schuller W, Bjorner JB. A confirmatory factor analysis approach was found to accurately estimate the reliability of transition ratings. J Clin Epidemiol. 2022;141:36-45. doi:10.1016/j.jclinepi.2021.08.029

Examples