Global Journal of Economics and Business

Volume 9 - Issue 3 (17) | PP: 706 - 716 Language : English
DOI : https://doi.org/10.31559/GJEB2020.9.3.17
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Binary logistic regression to measure the impact of social support to ability for encounter problems (an applied study on the employees of princess Noura bint Abdul Rahman university)

Karima Ahmed El Sayed ,
Inas Abu Bakr Helal
Received Date Revised Date Accepted Date Publication Date
30/6/2020 26/7/2020 12/9/2020 23/12/2020
Abstract
This study aims to try to identify the extent to which the dual logistic regression model can be used to measure the impact of social support for individuals on the ability to face problems to verify the validity of the research hypotheses or not, taking into account the types of social support according to the research hypotheses Family support, support for friends, information support and performance support (finance, work, interaction between others), where a questionnaire was prepared to serve the purposes of the research and distributed to a sample of 814 employees of Princess Noura bint Abdul Rahman who are over the age of 18, Among the most important results reached is that the use of logistic regression to represent the impact of social support on the ability to face problems was successful and highly efficient, as the results of the research showed that the explanation variance in the logistic regression model in the impact of social support on the ability of people to face problems 76% which is an very good ratio Also, all the results of the statistical tests of the model of the effect of support on the ability of the sample members to face problems give very good results, as all the results were in agreement with the research hypotheses that were established.


How To Cite This Article
Sayed , K. A. E. & Helal , I. A. B. (2020). Binary logistic regression to measure the impact of social support to ability for encounter problems (an applied study on the employees of princess Noura bint Abdul Rahman university) . Global Journal of Economics and Business, 9 (3), 706-716, 10.31559/GJEB2020.9.3.17

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