Comparing Regression versus Correction Formula Predictions of Passive Recall Test Scores from Yes-No Test Results
Raymond Stubbe
Kyushu Sangyo University
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A novel form of scoring formula for self-report yesno vocabulary tests
was presented in Stubbe and Stewart, based on multiple regression
models that use both real-word and pseudoword reports to predict
subsequent scores on a test of passive recall knowledge (as measured by
L2 to L1 translations). The aim of the present study is to determine how
well passive recall test scores can be predicted from yes-no test results
adjusted using two methods: (1) regression formulas versus (2) the four
established correction for guessing formulas outlined in Huibregtse,
Admiraal, and Meara: h-f, cfg, Δm and lsdt. After taking a yes-no test
followed by a passive recall test of the same 96 real-words, the sample of
Japanese university students (N 431) was split into two groups of
comparable proficiency (A and B). The original Stubbe and Stewart
regression formula was compared to the four correction formulas by
analyzing their application with the Group A. Despite having a lower
correlation with passive recall test scores than one of the correction
formulas, the predicted scores produced were significantly closer. A new
regression formula was then created using the Group A’s test results and
this was used to predict translation test scores on Group B, along with the
four correction formulas. As the resulting predictions were superior to
those of any of the correction formulas, and not significantly different
from the actual passive recall test scores, plus the correlation with these
translation test scores was the highest (0.845), it was concluded that
regression formulas produced the best predictions.

Stubbe, R. (2013). Comparing regression versus correction formula predictions of passive recall test scores from yesno test results. Vocabulary Learning and Instruction, 2 (1), 39-46. doi: 10.7820/vli.v02.1.stubbe