Adjust Estimates of Learning for Guessing
Calculate expected values for goodness of fit test
Count transitions between pre and post test responses
Constraints: Sum to 1
Constraints: Sum to 1
Goodness of fit statistics for transition matrix data
Format transition matrix result with appropriate row and column names
Group Level Adjustment That Accounts for Propensity to Guess
guess_lik
guess adjust estimates of learning for guessing related bias.
guessdk_lik
Interleave vectors
Person Level Adjustment
Calculate item level and aggregate learning
Bootstrapped standard errors of effect size estimates
Creates a transition matrix for each item.
No NAs
Standard Guessing Correction for Learning
transmat: Cross-wave transition matrix
Validate that two data frames have compatible dimensions
Validate that input is a data frame
Validate gamma parameter
Validate lucky vector for standard correction
Validate prior parameters
Validate transition matrix values
Provides tools to adjust estimates of learning for guessing-related bias in educational and survey research. Implements standard guessing correction methods and a sophisticated latent class model that leverages informative pre-post test transitions to account for guessing behavior. The package helps researchers obtain more accurate estimates of actual learning when respondents may guess on closed-ended knowledge items. For theoretical background and empirical validation, see Cor and Sood (2018) <https://gsood.com/research/papers/guess.pdf>.
Useful links