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Table 7 depicts dependence of 'perception of women entrepreneurs on the problem of negative attitude of banks towards women' based on father's occupations (variable 1), whereas it is independent of mother's (variable 2), husband's (variable 3) and kinsfolk's (variable 4) occupation.
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In the United States, five types of therapists (occupational, physical, respiratory, speech and "other") were captured with the occupation variable of the internationally released Current Population Survey microdata file.
In our study, we used a job level indicator, derived from the occupation variable.
In Table 14, H4D0 has been rejected thereby indicating a relationship between kinsfolk's occupation (variable 4) with the problem of high cost of technological acquisition.
Note also that the current income effects are greatly reduced when a proxy for permanent income (the father occupation variable) is controlled for.
This seems logical, as the occupation variable includes information about both the workers' productivity and their capacity to implement specific job activities.
Interestingly, the final model indicated that mobility had a positive influence on the occupation variable.
However, the occupation variable could not be included in the multivariate model due to substantial missing data.
Since housewives accounted for more than 10% of the total study population, these participants were grouped as 'housewife' in the occupation variable.
However, in our study, the results were not much different when we run the models e.g. with and without the occupation variable.
While the carer occupation variable was significantly associated with CSEBD, the disparities in odds ratios reflect differences in CSEBD by employment status rather than occupational skill.
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CEO of Professional Science Editing for Scientists @ prosciediting.com