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Pairwise Comparison in Repeated Measures

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Pairwise Comparison in Repeated Measures. / Oyeka, I.C.A.; Nnanatu, Chibuzor.
In: Journal of Modern Applied Statistical Methods, Vol. 13, No. 2, 2014, p. 151-168.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Oyeka, ICA & Nnanatu, C 2014, 'Pairwise Comparison in Repeated Measures', Journal of Modern Applied Statistical Methods, vol. 13, no. 2, pp. 151-168. https://doi.org/10.22237/jmasm/1414814820

APA

Oyeka, I. C. A., & Nnanatu, C. (2014). Pairwise Comparison in Repeated Measures. Journal of Modern Applied Statistical Methods, 13(2), 151-168. https://doi.org/10.22237/jmasm/1414814820

Vancouver

Oyeka ICA, Nnanatu C. Pairwise Comparison in Repeated Measures. Journal of Modern Applied Statistical Methods. 2014;13(2):151-168. doi: 10.22237/jmasm/1414814820

Author

Oyeka, I.C.A. ; Nnanatu, Chibuzor. / Pairwise Comparison in Repeated Measures. In: Journal of Modern Applied Statistical Methods. 2014 ; Vol. 13, No. 2. pp. 151-168.

Bibtex

@article{25171f72637b489caa008bd24de2e246,
title = "Pairwise Comparison in Repeated Measures",
abstract = "Sometimes a random sample of subjects or patients may be exposed to a battery of diagnostic tests or medication over time and interest is on determining whether there is progressive remission of condition, disease or symptom. Also perhaps early in a program or experiment, subjects or candidates may be required to significantly improve in their performance rates at the current trial relative to an immediately preceding trial, otherwise they may have to withdraw from or drop out. The research interest would then be to determine some critical minimum marginal success rate to guide the management in decision making as well as in policy implementation. Success rates lower than the minimum expected value would indicate a need for some remedial actions. A method of estimating these rates is proposed assuming that the requirement is at the second trial. Pairwise comparisons of proportions of success or failure by subjects or candidates in a sequence of experiments or trials over time or space are conducted to ascertain which subject or combinations is responsible for the rejection of the null hypothesis. The proposed methods is illustrated and shown to be at least as efficient and powerful as competitors.",
author = "I.C.A. Oyeka and Chibuzor Nnanatu",
note = "This Regular Article is brought to you for free and open access by the Open Access Journals at DigitalCommons@WayneState",
year = "2014",
doi = "10.22237/jmasm/1414814820",
language = "English",
volume = "13",
pages = "151--168",
journal = "Journal of Modern Applied Statistical Methods",
publisher = "Wayne State University",
number = "2",

}

RIS

TY - JOUR

T1 - Pairwise Comparison in Repeated Measures

AU - Oyeka, I.C.A.

AU - Nnanatu, Chibuzor

N1 - This Regular Article is brought to you for free and open access by the Open Access Journals at DigitalCommons@WayneState

PY - 2014

Y1 - 2014

N2 - Sometimes a random sample of subjects or patients may be exposed to a battery of diagnostic tests or medication over time and interest is on determining whether there is progressive remission of condition, disease or symptom. Also perhaps early in a program or experiment, subjects or candidates may be required to significantly improve in their performance rates at the current trial relative to an immediately preceding trial, otherwise they may have to withdraw from or drop out. The research interest would then be to determine some critical minimum marginal success rate to guide the management in decision making as well as in policy implementation. Success rates lower than the minimum expected value would indicate a need for some remedial actions. A method of estimating these rates is proposed assuming that the requirement is at the second trial. Pairwise comparisons of proportions of success or failure by subjects or candidates in a sequence of experiments or trials over time or space are conducted to ascertain which subject or combinations is responsible for the rejection of the null hypothesis. The proposed methods is illustrated and shown to be at least as efficient and powerful as competitors.

AB - Sometimes a random sample of subjects or patients may be exposed to a battery of diagnostic tests or medication over time and interest is on determining whether there is progressive remission of condition, disease or symptom. Also perhaps early in a program or experiment, subjects or candidates may be required to significantly improve in their performance rates at the current trial relative to an immediately preceding trial, otherwise they may have to withdraw from or drop out. The research interest would then be to determine some critical minimum marginal success rate to guide the management in decision making as well as in policy implementation. Success rates lower than the minimum expected value would indicate a need for some remedial actions. A method of estimating these rates is proposed assuming that the requirement is at the second trial. Pairwise comparisons of proportions of success or failure by subjects or candidates in a sequence of experiments or trials over time or space are conducted to ascertain which subject or combinations is responsible for the rejection of the null hypothesis. The proposed methods is illustrated and shown to be at least as efficient and powerful as competitors.

U2 - 10.22237/jmasm/1414814820

DO - 10.22237/jmasm/1414814820

M3 - Journal article

VL - 13

SP - 151

EP - 168

JO - Journal of Modern Applied Statistical Methods

JF - Journal of Modern Applied Statistical Methods

IS - 2

ER -