| Autor: |
Mohamad, Nor Amira, Ali, Zalila, Noor, Norlida Mohd, Baharum, Adam |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 2016, Vol. 1750 Issue 1, p1-11, 11p, 17 Charts |
| Abstrakt: |
Multinomial logistic regression is used to model the outcomes of a categorical dependent variable with more than two categories and predicts the probabilities of the different possible outcomes based on several independent variables. Mathematically, for k categories of the response variable, the multinomial logit model consists of k-1 binary logit model that estimate the effect of the predictors on the probability of success in that category, in comparison to the reference category. The development of the model consists of selection procedures used in selecting important predictor variable and diagnostics tools used to examine for multicollinearity and to detect strongly influential outliers. The overall model is evaluated using the goodness of fit tests and the pseudo Rsquares. The significance of each predictor variable is tested using the likelihood ratio test and the odds ratio is used to assess the contribution of individual predictors. This study used multinomial logistic regression model to determine stress level among secondary school teachers in Kubang Pasu district, Kedah based on their demographic profiles and workplace environment. The results indicated that the stress levels among school teachers are related to age, marital status, workload, job responsibility, and interaction between ages with job responsibility. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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