PARAMETER ESTIMATION FOR IMPROVING ASSOCIATION INDICATORS IN BINARY LOGISTIC REGRESSION

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

BASHIRI MAHDI; KAMRANRAD REZA

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: PRODUCTION AND OPERATIONS MANAGEMENT Year:2011 | Volume:2 | Issue:1 (2) Page(s): 135-154

Download Full-Text

Persian Verion

View:

816

Download:

Cites:

Information Journal Paper

Title

PARAMETER ESTIMATION FOR IMPROVING ASSOCIATION INDICATORS IN BINARY LOGISTIC REGRESSION

Author(s)

BASHIRI MAHDI | KAMRANRAD REZA | Issue Writer Certificate

Keywords

PARAMETER ESTIMATIONQ2

BINARY LOGISTIC REGRESSIONQ2

ASSOCIATION INDICATORQ2

CONCORDANT NUMBERQ2

MEMBERSHIP DEGREEQ2

Abstract

The aim of this paper is to estimate the parameters of BINARY LOGISTIC REGRESSION model for maximizing the log-likelihood function with improved ASSOCIATION INDICATORs. Logistic regression, similar to other PARAMETER ESTIMATION approaches, requires an indicator for the estimation appropriateness of its parameters, one of which is the ASSOCIATION INDICATOR. The ASSOCIATION INDICATORs demonstrate the frequency of success responses occurred against failure in certain number of Bernoulli independent experiments. In PARAMETER ESTIMATION, existing indicators' values are not sensitive to the parameter values, whereas the proposed indicators are sensitive to the estimated parameters during the iterative procedure. Therefore, the innovation of this study is in proposing a new ASSOCIATION INDICATOR of BINARY LOGISTIC REGRESSION with more sensitivity to the estimated parameters in maximizing the log-likelihood in iterative procedure. Findings of an example analysis and their comparison with ASSOCIATION INDICATORs imply higher accuracy and appropriateness of the proposed indicators.

Cites

No record.

References

No record.

Cite

APA: Copy

BASHIRI, MAHDI, & KAMRANRAD, REZA. (2011). PARAMETER ESTIMATION FOR IMPROVING ASSOCIATION INDICATORS IN BINARY LOGISTIC REGRESSION. PRODUCTION AND OPERATIONS MANAGEMENT, 2(1 (2)), 135-154. SID. https://sid.ir/paper/379065/en

Vancouver: Copy

BASHIRI MAHDI, KAMRANRAD REZA. PARAMETER ESTIMATION FOR IMPROVING ASSOCIATION INDICATORS IN BINARY LOGISTIC REGRESSION. PRODUCTION AND OPERATIONS MANAGEMENT[Internet]. 2011;2(1 (2)):135-154. Available from: https://sid.ir/paper/379065/en

IEEE: Copy

MAHDI BASHIRI, and REZA KAMRANRAD, “PARAMETER ESTIMATION FOR IMPROVING ASSOCIATION INDICATORS IN BINARY LOGISTIC REGRESSION,” PRODUCTION AND OPERATIONS MANAGEMENT, vol. 2, no. 1 (2), pp. 135–154, 2011, [Online]. Available: https://sid.ir/paper/379065/en

Related Journal Papers