Trial-and-chance success.

2011 ◽  
pp. 333-346
Author(s):  
William F. Bruce ◽  
Frank S. Freeman
Keyword(s):  
Chance Success

The Correction for Chance Success in Carrying out Experiments According to the Method of Constant Stimuli

Vestnik MEI ◽  
2019 ◽  
Vol 6 ◽  
pp. 71-76
Author(s):  
Georgiy V. Boos ◽  
◽  
Andrey A. Grigoryev ◽  
Viktoriya A. Rybina ◽  
◽  
...  
Keyword(s):  
Chance Success ◽  
Method Of Constant Stimuli

An index of item validity providing a correction for chance success

Psychometrika ◽  
1947 ◽  
Vol 12 (1) ◽  
pp. 51-58 ◽  
Author(s):  
A. P. Johnson
Keyword(s):  
Chance Success

Element of Chance and Comparative Reliability of Matching Tests and Multiple-Choice Tests

1982 ◽  
Vol 50 (3) ◽  
pp. 975-980 ◽  
Author(s):  
Donald W. Zimmerman ◽  
Richard H. Williams
Keyword(s):  
Explicit Formula ◽  
Multiple Choice ◽  
Multiple Choice Tests ◽  
Test Parameters ◽  
Choice Tests ◽  
Source Of Error ◽  
Reliability Coefficients ◽  
Chance Success

Simple formulas for the reliability of matching tests and multiple-choice tests, based on the assumption that chance success by guessing is the only source of error variation, are derived. The reliabilities of the two types of tests are compared, and an explicit formula relating their reliability coefficients when relevant test parameters remain fixed is presented. It is found that, in the majority of cases which are likely in practice, matching tests are considerably less fallible than multiple-choice tests.

Multiple-Answer Items and Chance Success

1965 ◽  
Vol 16 (3_suppl) ◽  
pp. 1011-1012
Author(s):  
Lewis R. Aiken
Keyword(s):  
General Formula ◽  
Correct Answer ◽  
Test Item ◽  
Hypergeometric Distribution ◽  
Objective Test ◽  
Occupancy Problem ◽  
One To One ◽  
Special Case ◽  
Chance Success

The use of a general formula, the solution to a special case of the classical occupancy problem, for estimating the probability of chance success on any one-to-one objective test item is reviewed. It is noted that it may on occasion be more appropriate to write items with more than one correct answer and that the chance success formula for this situation is the hypergeometric distribution.

scholarly journals The effect of the correction of self-assessment-based chance success on psychometric characteristics of the test

2018 ◽  
Vol 8 (3) ◽  
pp. 567-598
Author(s):  
Didem Özdoğan ◽  
Nuri Doğan
Keyword(s):  
Test Validity ◽  
Statistical Analyses ◽  
Psychometric Characteristics ◽  
Self Assessment ◽  
Correction Formula ◽  
Correction For Guessing ◽  
The Difference ◽  
Chance Success

This study examines the effect of self-assessment-based chance success on psychometric characteristics of the test. First, the data was cleared of chance success by means of correction-for-guessing formula and self-assessment, and then statistical analyses were conducted. Item discriminations showed an increase when the correction-for-guessing formula was used; and when self-assessment was used, they showed variability. Test validity increased when correction formula was used; and when self-assessment was used, a slight decrease was observed. Besides, this study examined the effect of correction for chance success upon corrected self-assessment based on IRT guessing parameter. It was observed that the data that were not corrected in accordance with chance scores had higher guessing parameters than those corrected in accordance with self-assessment. In addition, it was evident that the difference between the guessing parameters of the uncorrected data and the data cleared of chance scores by means of self-assessment was significant. It was also revealed that the correction of self-assessment-based chance success have an advantage over classical correction for guessing formula on psychometric characteristics of the test.

Effect of Chance Success Due to Guessing on Error of Measurement in Multiple-Choice Tests

1965 ◽  
Vol 16 (3_suppl) ◽  
pp. 1193-1196 ◽  
Author(s):  
Donald W. Zimmerman ◽  
Richard H. Williams
Keyword(s):  
Multiple Choice ◽  
Error Variance ◽  
Choice Test ◽  
Multiple Choice Test ◽  
Minimum Standard ◽  
Multiple Choice Tests ◽  
Choice Tests ◽  
Standard Error Of Measurement ◽  
Error Of Measurement ◽  
Chance Success

Chance success due to guessing is treated as a component of the error variance of a multiple-choice test score. It is shown that for a test of given item structure the minimum standard error of measurement can be estimated by the formula (N−X)/a. where N is the total number of items, X is the score, and a is the number of alternative choices per item. The significance of non-independence of true score and this component of error score on multiple-choice tests is discussed.

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