JBS_I2Leave
Temi A. Sorungbe
August 4, 2016
Executive Summary
This document ananlyses the relationship between intent to leave and job satisfaction. Specifically intent to leave is anala ysed as an outcome of job satisfaction and other demographic variables.
Correlations in the job satisfaction dataset reveal no job satisfaction and/or demograohic variables are highly correlated (ei.e correlations > 0.5) with intent to leave and no job satisfaction or demographic variables are highly correlated with intent to leave Nigeria.
In addition, there is a 0.316 correation between Intent to leave work and Intent to leave Nigeria.
A logistic regression model is used in addition to the nested model approach to test various models. The best model is determined using residuals, influence measures and inference tests.
## Warning: package 'caret' was built under R version 3.2.5SUMMARY STATISTICS
Below are proportions (in percent) of all demographic and job satisfaction variables in the data.
## Warning in rm(skills_salary, meds_available, printd_materials,
## workin_hrs, : object 'workin_hrs' not found## Warning in rm(skills_salary, meds_available, printd_materials,
## workin_hrs, : object 'quant_of_work' not found## Warning in rm(skills_salary, meds_available, printd_materials,
## workin_hrs, : object 'work_allocatn' not found## Warning in rm(skills_salary, meds_available, printd_materials,
## workin_hrs, : object 'support_provided' not found## Warning in rm(skills_salary, meds_available, printd_materials,
## workin_hrs, : object 'duties_skills' not found## Warning in rm(skills_salary, meds_available, printd_materials,
## workin_hrs, : object 'prof_respon' not found## $wexp
##
## <= 3years 3+ to 5years 5+ to 10years 10+ to 15years 15+years
## 19.33333 18.66667 32.66667 19.33333 10.00000
##
## $age
##
## <= 30years 30-39years >=40years
## 40.00000 37.33333 22.66667
##
## $gender
##
## Female Male
## 88.66667 11.33333
##
## $profession
##
## CHEW Other
## 60.66667 39.33333
##
## $education
##
## Secondary Tertiary
## 2 98
##
## $work_distance
##
## <= 1hour > 1hour
## 96 4
##
## $overall_jbs
##
## Dissatisfied Neutral Satisfied Very dissatisfied
## 6.00000 14.00000 61.33333 2.00000
## Very satisfied
## 16.66667
##
## $salaray_level
##
## Dissatisfied Neutral Satisfied Very dissatisfied
## 44.666667 15.333333 35.333333 2.666667
## Very satisfied
## 2.000000
##
## $allowance
##
## Dissatisfied Neutral Satisfied Very dissatisfied
## 44.666667 15.333333 35.333333 2.666667
## Very satisfied
## 2.000000
##
## $coverage_level
##
## Dissatisfied Neutral Satisfied Very dissatisfied
## 34.666667 21.333333 38.000000 4.666667
## Very satisfied
## 1.333333
##
## $skills_salary
##
## Dissatisfied Neutral Satisfied Very dissatisfied
## 40.666667 16.000000 36.666667 5.333333
## Very satisfied
## 1.333333
##
## $salary_work_vol
##
## Dissatisfied Neutral Satisfied Very dissatisfied
## 43.918919 14.189189 35.810811 4.729730
## Very satisfied
## 1.351351
##
## $meds_available
##
## Dissatisfied Neutral Satisfied Very satisfied
## 12.66667 17.33333 64.00000 6.00000
##
## $skills_salary
##
## Dissatisfied Neutral Satisfied Very dissatisfied
## 40.666667 16.000000 36.666667 5.333333
## Very satisfied
## 1.333333
##
## $meds_available
##
## Dissatisfied Neutral Satisfied Very satisfied
## 12.66667 17.33333 64.00000 6.00000
##
## $printd_materials
##
## Dissatisfied Neutral Satisfied Very dissatisfied
## 10.7382550 10.0671141 72.4832215 0.6711409
## Very satisfied
## 6.0402685
##
## $workin_hrs
##
## Dissatisfied Neutral Satisfied Very dissatisfied
## 5.3333333 10.6666667 78.6666667 0.6666667
## Very satisfied
## 4.6666667
##
## $quant_of_work
##
## Dissatisfied Neutral Satisfied Very dissatisfied
## 15.3333333 18.6666667 61.3333333 0.6666667
## Very satisfied
## 4.0000000
##
## $work_allocatn
##
## Dissatisfied Neutral Satisfied Very dissatisfied
## 14.6666667 17.3333333 63.3333333 0.6666667
## Very satisfied
## 4.0000000
##
## $div_work_hrs
##
## Dissatisfied Neutral Satisfied Very dissatisfied
## 9.3333333 15.3333333 71.3333333 0.6666667
## Very satisfied
## 3.3333333
##
## $support_provided
##
## Dissatisfied Neutral Satisfied Very satisfied
## 4.000000 8.000000 82.666667 5.333333
##
## $consumables
##
## Dissatisfied Neutral Satisfied Very dissatisfied
## 10.666667 12.000000 71.333333 1.333333
## Very satisfied
## 4.666667
##
## $duties_skills
##
## Dissatisfied Neutral Satisfied Very satisfied
## 4.666667 8.666667 81.333333 5.333333
##
## $prof_respon
##
## Dissatisfied Neutral Satisfied Very satisfied
## 4.666667 6.000000 80.000000 9.333333
##
## $protectn_gear
##
## Dissatisfied Neutral Satisfied Very dissatisfied
## 20.000000 18.000000 55.333333 2.666667
## Very satisfied
## 4.000000
##
## $printed_materials.
##
## Dissatisfied Neutral Satisfied Very dissatisfied
## 10.7382550 10.0671141 72.4832215 0.6711409
## Very satisfied
## 6.0402685
##
## $workin_hrs.
##
## Dissatisfied Neutral Satisfied Very dissatisfied
## 5.3333333 10.6666667 78.6666667 0.6666667
## Very satisfied
## 4.6666667
##
## $quant_of_work.
##
## Dissatisfied Neutral Satisfied Very dissatisfied
## 15.3333333 18.6666667 61.3333333 0.6666667
## Very satisfied
## 4.0000000
##
## $work_allocatn
##
## Dissatisfied Neutral Satisfied Very dissatisfied
## 14.6666667 17.3333333 63.3333333 0.6666667
## Very satisfied
## 4.0000000
##
## $anc_selectn_4trainin
##
## Dissatisfied Neutral Satisfied Very dissatisfied
## 11.333333 10.666667 72.000000 2.666667
## Very satisfied
## 3.333333
##
## $tranin_recvd_needs
## numeric(0)
##
## $applyin_knw_recvd
##
## Dissatisfied Neutral Satisfied Very dissatisfied
## 14.000000 8.666667 65.333333 2.666667
## Very satisfied
## 9.333333
##
## $skills_acquired
##
## Dissatisfied Neutral Satisfied Very dissatisfied
## 12.000000 8.000000 71.333333 2.666667
## Very satisfied
## 6.000000
##
## $promotn_opport
##
## Dissatisfied Neutral Satisfied Very dissatisfied
## 6.7114094 8.0536913 70.4697987 0.6711409
## Very satisfied
## 14.0939597
##
## $div_workin_hrs
##
## Dissatisfied Neutral Satisfied Very dissatisfied
## 9.3333333 15.3333333 71.3333333 0.6666667
## Very satisfied
## 3.3333333
##
## $support_provided.
##
## Dissatisfied Neutral Satisfied Very satisfied
## 4.000000 8.000000 82.666667 5.333333
##
## $duties_variety.
##
## Dissatisfied Neutral Satisfied Very satisfied
## 3.333333 10.666667 82.000000 4.000000
##
## $duties_skills
##
## Dissatisfied Neutral Satisfied Very satisfied
## 4.666667 8.666667 81.333333 5.333333
##
## $job_stability
##
## Dissatisfied Neutral Satisfied Very satisfied
## 7.3333333 16.0000000 76.0000000 0.6666667
##
## $X.allowance_regularity
##
## Dissatisfied Neutral Satisfied Very dissatisfied
## 36.66667 22.66667 36.66667 2.00000
## Very satisfied
## 2.00000
##
## $workplace_reinforcement
##
## Dissatisfied Neutral Satisfied Very dissatisfied
## 11.3333333 21.3333333 65.3333333 0.6666667
## Very satisfied
## 1.3333333
##
## $decisn_makin
##
## Dissatisfied Neutral Satisfied Very dissatisfied
## 10.6666667 22.0000000 65.3333333 0.6666667
## Very satisfied
## 1.3333333
##
## $prof_respon
##
## Dissatisfied Neutral Satisfied Very satisfied
## 4.666667 6.000000 80.000000 9.333333
##
## $Leave.work
##
## No Yes
## 30.66667 69.33333
##
## $Leave.Nigeria
##
## No Yes
## 34 66## row col
## skills_salary 7 6
## salary_work_vol 8 6
## coverage_level 6 7
## salary_work_vol 8 7
## coverage_level 6 8
## skills_salary 7 8
## anc_selectn_4trainin 26 25
## applyin_knw_recvd 28 25
## skills_acquired 29 25
## trainin_recvd 25 26
## trainin_recvd_needs 27 26
## applyin_knw_recvd 28 26
## skills_acquired 29 26
## anc_selectn_4trainin 26 27
## applyin_knw_recvd 28 27
## skills_acquired 29 27
## trainin_recvd 25 28
## anc_selectn_4trainin 26 28
## trainin_recvd_needs 27 28
## skills_acquired 29 28
## trainin_recvd 25 29
## anc_selectn_4trainin 26 29
## trainin_recvd_needs 27 29
## applyin_knw_recvd 28 29MODEL FITTING - DEMOGRAPHICS
Results from logistic regression models with ouctome - intent to leave work and demograohic variables as regressors of interest. Variance Inflation rate of “age” across all models:
## [1] 0.2321871 0.2707364 0.2740295 0.2861106 0.2884212 0.2950141## Analysis of Deviance Table
##
## Model 1: hcp2_f$Leave.work - 1 ~ 1
## Model 2: hcp2_f$Leave.work - 1 ~ hcp2_f$age
## Model 3: hcp2_f$Leave.work - 1 ~ hcp2_f$age + hcp2_f$wexp
## Model 4: hcp2_f$Leave.work - 1 ~ hcp2_f$age + hcp2_f$wexp + hcp2_f$gender
## Model 5: hcp2_f$Leave.work - 1 ~ hcp2_f$age + hcp2_f$wexp + hcp2_f$gender +
## hcp2_f$prof
## Model 6: hcp2_f$Leave.work - 1 ~ hcp2_f$age + +hcp2_f$wexp + hcp2_f$gender +
## hcp2_f$prof + hcp2_f$educ
## Model 7: hcp2_f$Leave.work - 1 ~ hcp2_f$age + +hcp2_f$wexp + hcp2_f$gender +
## hcp2_f$prof + hcp2_f$educ + hcp2_f$wkdist
## Resid. Df Resid. Dev Df Deviance Pr(>Chi)
## 1 145 178.71
## 2 144 178.28 1 0.4354 0.5093
## 3 143 178.18 1 0.0903 0.7637
## 4 142 177.54 1 0.6399 0.4237
## 5 141 177.46 1 0.0811 0.7758
## 6 140 175.51 1 1.9508 0.1625
## 7 139 171.29 1 4.2264 0.0398 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Results explained
Age and work experience in years are correlated (0.506) and might explain the little improvement gained on deviance when comparing age as the only regressor of interest versus age and work experience as regressors of interests in the regression models.
Also, although the residual deviance reduces with inclusion of more regressors, variance inflation rate (VIF) of the first regressor “age” shows that work experience and profession may be unnecessary variables as the VIF of age increases more with inclusion of these two regressors in the regressor models.
Finally, ANOVA results show the inclusion of work distance results in a regression model significantly different from the null model in predicting the expected value of the outcome - intent to leave work.
Thererfore, from the results, i believe work distance should be the only demographic predictor included in the intent to leave regression model.
MODEL FITTING - JOB SATISFACTION
Results from logistic regression models with ouctome - intent to leave work - using only job satisfaction (jbs) variables as regressors of interest. The effect of colinearity of job satisfaction variables is avoided by including uncorrelated jbs variables in the regression models (see appendix for correlation matrix). Variance Inflation rate “overall job satisfaction” across all models:
## [1] 0.3353460 0.3389867 0.3432921 0.3498417 0.3502022 0.3561011 0.3619029
## [8] 0.3734225 0.3813004 0.3828265 0.3903108 0.4024047 0.4500018 0.4461868
## [15] 0.4666556 0.4729368 0.4721662 0.4726757 0.4645707 0.4636162 0.4647850
## [22] 0.4643179 0.4647572 0.4641402 0.5032645 0.5053206 0.5155430 0.5280298
## [29] 0.5327681 0.6565300## Analysis of Deviance Table
##
## Model 1: hcp2_f$Leave.work - 1 ~ 1
## Model 2: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn
## Model 3: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn + hcp2_f$allowances
## Model 4: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn + hcp2_f$allowances +
## hcp2_f$skills_salary
## Model 5: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn + hcp2_f$allowances +
## hcp2_f$skills_salary + hcp2_f$meds_available
## Model 6: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn + hcp2_f$allowances +
## hcp2_f$skills_salary + hcp2_f$meds_available + hcp2_f$consumables
## Model 7: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn + hcp2_f$allowances +
## hcp2_f$skills_salary + hcp2_f$meds_available + hcp2_f$consumables +
## hcp2_f$protectn_gear
## Model 8: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn + hcp2_f$allowances +
## hcp2_f$skills_salary + hcp2_f$meds_available + hcp2_f$consumables +
## hcp2_f$protectn_gear + hcp2_f$printed_materials
## Model 9: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn + hcp2_f$allowances +
## hcp2_f$skills_salary + hcp2_f$meds_available + hcp2_f$consumables +
## hcp2_f$protectn_gear + hcp2_f$printed_materials + hcp2_f$workin_hrs
## Model 10: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn + hcp2_f$allowances +
## hcp2_f$skills_salary + hcp2_f$meds_available + hcp2_f$consumables +
## hcp2_f$protectn_gear + hcp2_f$printed_materials + hcp2_f$workin_hrs +
## hcp2_f$quant_of_work
## Model 11: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn + hcp2_f$allowances +
## hcp2_f$skills_salary + hcp2_f$meds_available + hcp2_f$consumables +
## hcp2_f$protectn_gear + hcp2_f$printed_materials + hcp2_f$workin_hrs +
## hcp2_f$quant_of_work + hcp2_f$work_allocatn
## Model 12: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn + hcp2_f$allowances +
## hcp2_f$skills_salary + hcp2_f$meds_available + hcp2_f$consumables +
## hcp2_f$protectn_gear + hcp2_f$printed_materials + hcp2_f$workin_hrs +
## hcp2_f$quant_of_work + hcp2_f$work_allocatn + hcp2_f$div_workin_hrs
## Model 13: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn + hcp2_f$allowances +
## hcp2_f$skills_salary + hcp2_f$meds_available + hcp2_f$consumables +
## hcp2_f$protectn_gear + hcp2_f$printed_materials + hcp2_f$workin_hrs +
## hcp2_f$quant_of_work + hcp2_f$work_allocatn + hcp2_f$div_workin_hrs +
## hcp2_f$support_provided
## Model 14: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn + hcp2_f$allowances +
## hcp2_f$skills_salary + hcp2_f$meds_available + hcp2_f$consumables +
## hcp2_f$protectn_gear + hcp2_f$printed_materials + hcp2_f$workin_hrs +
## hcp2_f$quant_of_work + hcp2_f$work_allocatn + hcp2_f$div_workin_hrs +
## hcp2_f$support_provided + hcp2_f$duties_variety
## Model 15: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn + hcp2_f$allowances +
## hcp2_f$skills_salary + hcp2_f$meds_available + hcp2_f$consumables +
## hcp2_f$protectn_gear + hcp2_f$printed_materials + hcp2_f$workin_hrs +
## hcp2_f$quant_of_work + hcp2_f$work_allocatn + hcp2_f$div_workin_hrs +
## hcp2_f$support_provided + hcp2_f$duties_variety + hcp2_f$duties_skills
## Model 16: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn + hcp2_f$allowances +
## hcp2_f$skills_salary + hcp2_f$meds_available + hcp2_f$consumables +
## hcp2_f$protectn_gear + hcp2_f$printed_materials + hcp2_f$workin_hrs +
## hcp2_f$quant_of_work + hcp2_f$work_allocatn + hcp2_f$div_workin_hrs +
## hcp2_f$support_provided + hcp2_f$duties_variety + hcp2_f$duties_skills +
## hcp2_f$prof_respon
## Model 17: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn + hcp2_f$allowances +
## hcp2_f$skills_salary + hcp2_f$meds_available + hcp2_f$consumables +
## hcp2_f$protectn_gear + hcp2_f$printed_materials + hcp2_f$workin_hrs +
## hcp2_f$quant_of_work + hcp2_f$work_allocatn + hcp2_f$div_workin_hrs +
## hcp2_f$support_provided + hcp2_f$duties_variety + hcp2_f$duties_skills +
## hcp2_f$prof_respon + hcp2_f$harmony_anc_team + hcp2_f$recognitn_colleague
## Model 18: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn + hcp2_f$allowances +
## hcp2_f$skills_salary + hcp2_f$meds_available + hcp2_f$consumables +
## hcp2_f$protectn_gear + hcp2_f$printed_materials + hcp2_f$workin_hrs +
## hcp2_f$quant_of_work + hcp2_f$work_allocatn + hcp2_f$div_workin_hrs +
## hcp2_f$support_provided + hcp2_f$duties_variety + hcp2_f$duties_skills +
## hcp2_f$prof_respon + hcp2_f$harmony_anc_team + hcp2_f$recognitn_colleague
## Model 19: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn + hcp2_f$allowances +
## hcp2_f$skills_salary + hcp2_f$meds_available + hcp2_f$consumables +
## hcp2_f$protectn_gear + hcp2_f$printed_materials + hcp2_f$workin_hrs +
## hcp2_f$quant_of_work + hcp2_f$work_allocatn + hcp2_f$div_workin_hrs +
## hcp2_f$support_provided + hcp2_f$duties_variety + hcp2_f$duties_skills +
## hcp2_f$prof_respon + hcp2_f$harmony_anc_team + hcp2_f$recognitn_colleague +
## hcp2_f$recognitn_bosses
## Model 20: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn + hcp2_f$allowances +
## hcp2_f$skills_salary + hcp2_f$meds_available + hcp2_f$consumables +
## hcp2_f$protectn_gear + hcp2_f$printed_materials + hcp2_f$workin_hrs +
## hcp2_f$quant_of_work + hcp2_f$work_allocatn + hcp2_f$div_workin_hrs +
## hcp2_f$support_provided + hcp2_f$duties_variety + hcp2_f$duties_skills +
## hcp2_f$prof_respon + hcp2_f$harmony_anc_team + hcp2_f$recognitn_colleague +
## hcp2_f$recognitn_bosses + hcp2_f$respect_bosses
## Model 21: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn + hcp2_f$allowances +
## hcp2_f$skills_salary + hcp2_f$meds_available + hcp2_f$consumables +
## hcp2_f$protectn_gear + hcp2_f$printed_materials + hcp2_f$workin_hrs +
## hcp2_f$quant_of_work + hcp2_f$work_allocatn + hcp2_f$div_workin_hrs +
## hcp2_f$support_provided + hcp2_f$duties_variety + hcp2_f$duties_skills +
## hcp2_f$prof_respon + hcp2_f$harmony_anc_team + hcp2_f$recognitn_colleague +
## hcp2_f$recognitn_bosses + hcp2_f$respect_bosses + hcp2_f$anc_selectn_4trainin
## Model 22: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn + hcp2_f$allowances +
## hcp2_f$skills_salary + hcp2_f$meds_available + hcp2_f$consumables +
## hcp2_f$protectn_gear + hcp2_f$printed_materials + hcp2_f$workin_hrs +
## hcp2_f$quant_of_work + hcp2_f$work_allocatn + hcp2_f$div_workin_hrs +
## hcp2_f$support_provided + hcp2_f$duties_variety + hcp2_f$duties_skills +
## hcp2_f$prof_respon + hcp2_f$harmony_anc_team + hcp2_f$recognitn_colleague +
## hcp2_f$recognitn_bosses + hcp2_f$respect_bosses + hcp2_f$anc_selectn_4trainin +
## hcp2_f$promotn_opport
## Model 23: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn + hcp2_f$allowances +
## hcp2_f$skills_salary + hcp2_f$meds_available + hcp2_f$consumables +
## hcp2_f$protectn_gear + hcp2_f$printed_materials + hcp2_f$workin_hrs +
## hcp2_f$quant_of_work + hcp2_f$work_allocatn + hcp2_f$div_workin_hrs +
## hcp2_f$support_provided + hcp2_f$duties_variety + hcp2_f$duties_skills +
## hcp2_f$prof_respon + hcp2_f$harmony_anc_team + hcp2_f$recognitn_colleague +
## hcp2_f$recognitn_bosses + hcp2_f$respect_bosses + hcp2_f$anc_selectn_4trainin +
## hcp2_f$promotn_opport + hcp2_f$work_quality
## Model 24: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn + hcp2_f$allowances +
## hcp2_f$skills_salary + hcp2_f$meds_available + hcp2_f$consumables +
## hcp2_f$protectn_gear + hcp2_f$printed_materials + hcp2_f$workin_hrs +
## hcp2_f$quant_of_work + hcp2_f$work_allocatn + hcp2_f$div_workin_hrs +
## hcp2_f$support_provided + hcp2_f$duties_variety + hcp2_f$duties_skills +
## hcp2_f$prof_respon + hcp2_f$harmony_anc_team + hcp2_f$recognitn_colleague +
## hcp2_f$recognitn_bosses + hcp2_f$respect_bosses + hcp2_f$anc_selectn_4trainin +
## hcp2_f$promotn_opport + hcp2_f$work_quality + hcp2_f$prof_popular_image
## Model 25: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn + hcp2_f$allowances +
## hcp2_f$skills_salary + hcp2_f$meds_available + hcp2_f$consumables +
## hcp2_f$protectn_gear + hcp2_f$printed_materials + hcp2_f$workin_hrs +
## hcp2_f$quant_of_work + hcp2_f$work_allocatn + hcp2_f$div_workin_hrs +
## hcp2_f$support_provided + hcp2_f$duties_variety + hcp2_f$duties_skills +
## hcp2_f$prof_respon + hcp2_f$harmony_anc_team + hcp2_f$recognitn_colleague +
## hcp2_f$recognitn_bosses + hcp2_f$respect_bosses + hcp2_f$anc_selectn_4trainin +
## hcp2_f$promotn_opport + hcp2_f$work_quality + hcp2_f$prof_popular_image +
## hcp2_f$payment_regularity
## Model 26: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn + hcp2_f$allowances +
## hcp2_f$skills_salary + hcp2_f$meds_available + hcp2_f$consumables +
## hcp2_f$protectn_gear + hcp2_f$printed_materials + hcp2_f$workin_hrs +
## hcp2_f$quant_of_work + hcp2_f$work_allocatn + hcp2_f$div_workin_hrs +
## hcp2_f$support_provided + hcp2_f$duties_variety + hcp2_f$duties_skills +
## hcp2_f$prof_respon + hcp2_f$harmony_anc_team + hcp2_f$recognitn_colleague +
## hcp2_f$recognitn_bosses + hcp2_f$respect_bosses + hcp2_f$anc_selectn_4trainin +
## hcp2_f$promotn_opport + hcp2_f$work_quality + hcp2_f$prof_popular_image +
## hcp2_f$payment_regularity + hcp2_f$job_stability
## Model 27: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn + hcp2_f$allowances +
## hcp2_f$skills_salary + hcp2_f$meds_available + hcp2_f$consumables +
## hcp2_f$protectn_gear + hcp2_f$printed_materials + hcp2_f$workin_hrs +
## hcp2_f$quant_of_work + hcp2_f$work_allocatn + hcp2_f$div_workin_hrs +
## hcp2_f$support_provided + hcp2_f$duties_variety + hcp2_f$duties_skills +
## hcp2_f$prof_respon + hcp2_f$harmony_anc_team + hcp2_f$recognitn_colleague +
## hcp2_f$recognitn_bosses + hcp2_f$respect_bosses + hcp2_f$anc_selectn_4trainin +
## hcp2_f$promotn_opport + hcp2_f$work_quality + hcp2_f$prof_popular_image +
## hcp2_f$payment_regularity + hcp2_f$job_stability + hcp2_f$allowance_regularity
## Model 28: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn + hcp2_f$allowances +
## hcp2_f$skills_salary + hcp2_f$meds_available + hcp2_f$consumables +
## hcp2_f$protectn_gear + hcp2_f$printed_materials + hcp2_f$workin_hrs +
## hcp2_f$quant_of_work + hcp2_f$work_allocatn + hcp2_f$div_workin_hrs +
## hcp2_f$support_provided + hcp2_f$duties_variety + hcp2_f$duties_skills +
## hcp2_f$prof_respon + hcp2_f$harmony_anc_team + hcp2_f$recognitn_colleague +
## hcp2_f$recognitn_bosses + hcp2_f$respect_bosses + hcp2_f$anc_selectn_4trainin +
## hcp2_f$promotn_opport + hcp2_f$work_quality + hcp2_f$prof_popular_image +
## hcp2_f$payment_regularity + hcp2_f$job_stability + hcp2_f$allowance_regularity +
## hcp2_f$workplace_reinforcement
## Model 29: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn + hcp2_f$allowances +
## hcp2_f$skills_salary + hcp2_f$meds_available + hcp2_f$consumables +
## hcp2_f$protectn_gear + hcp2_f$printed_materials + hcp2_f$workin_hrs +
## hcp2_f$quant_of_work + hcp2_f$work_allocatn + hcp2_f$div_workin_hrs +
## hcp2_f$support_provided + hcp2_f$duties_variety + hcp2_f$duties_skills +
## hcp2_f$prof_respon + hcp2_f$harmony_anc_team + hcp2_f$recognitn_colleague +
## hcp2_f$recognitn_bosses + hcp2_f$respect_bosses + hcp2_f$anc_selectn_4trainin +
## hcp2_f$promotn_opport + hcp2_f$work_quality + hcp2_f$prof_popular_image +
## hcp2_f$payment_regularity + hcp2_f$job_stability + hcp2_f$allowance_regularity +
## hcp2_f$workplace_reinforcement + hcp2_f$decisn_makin
## Model 30: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn + hcp2_f$allowances +
## hcp2_f$skills_salary + hcp2_f$meds_available + hcp2_f$consumables +
## hcp2_f$protectn_gear + hcp2_f$printed_materials + hcp2_f$workin_hrs +
## hcp2_f$quant_of_work + hcp2_f$work_allocatn + hcp2_f$div_workin_hrs +
## hcp2_f$support_provided + hcp2_f$duties_variety + hcp2_f$duties_skills +
## hcp2_f$prof_respon + hcp2_f$harmony_anc_team + hcp2_f$recognitn_colleague +
## hcp2_f$recognitn_bosses + hcp2_f$respect_bosses + hcp2_f$anc_selectn_4trainin +
## hcp2_f$promotn_opport + hcp2_f$work_quality + hcp2_f$prof_popular_image +
## hcp2_f$payment_regularity + hcp2_f$job_stability + hcp2_f$allowance_regularity +
## hcp2_f$workplace_reinforcement + hcp2_f$decisn_makin + hcp2_f$perf_info_anc
## Model 31: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn + hcp2_f$allowances +
## hcp2_f$skills_salary + hcp2_f$meds_available + hcp2_f$consumables +
## hcp2_f$protectn_gear + hcp2_f$printed_materials + hcp2_f$workin_hrs +
## hcp2_f$quant_of_work + hcp2_f$work_allocatn + hcp2_f$div_workin_hrs +
## hcp2_f$support_provided + hcp2_f$duties_variety + hcp2_f$duties_skills +
## hcp2_f$prof_respon + hcp2_f$harmony_anc_team + hcp2_f$recognitn_colleague +
## hcp2_f$recognitn_bosses + hcp2_f$respect_bosses + hcp2_f$anc_selectn_4trainin +
## hcp2_f$promotn_opport + hcp2_f$work_quality + hcp2_f$prof_popular_image +
## hcp2_f$payment_regularity + hcp2_f$job_stability + hcp2_f$allowance_regularity +
## hcp2_f$workplace_reinforcement + hcp2_f$decisn_makin + hcp2_f$perf_info_anc +
## hcp2_f$employment_status
## Resid. Df Resid. Dev Df Deviance Pr(>Chi)
## 1 145 178.71
## 2 144 177.02 1 1.6915 0.19340
## 3 143 176.95 1 0.0709 0.79009
## 4 142 173.33 1 3.6142 0.05729 .
## 5 141 171.30 1 2.0318 0.15404
## 6 140 168.04 1 3.2652 0.07076 .
## 7 139 168.02 1 0.0131 0.90873
## 8 138 167.33 1 0.6947 0.40458
## 9 137 166.91 1 0.4155 0.51917
## 10 136 166.64 1 0.2772 0.59857
## 11 135 166.63 1 0.0050 0.94389
## 12 134 165.55 1 1.0821 0.29822
## 13 133 164.20 1 1.3456 0.24604
## 14 132 161.16 1 3.0412 0.08118 .
## 15 131 160.87 1 0.2962 0.58628
## 16 130 160.07 1 0.7908 0.37385
## 17 128 159.84 2 0.2349 0.88917
## 18 128 159.84 0 0.0000
## 19 127 159.58 1 0.2613 0.60924
## 20 126 156.06 1 3.5221 0.06056 .
## 21 125 154.98 1 1.0788 0.29898
## 22 124 153.34 1 1.6355 0.20094
## 23 123 153.26 1 0.0830 0.77325
## 24 122 153.19 1 0.0675 0.79494
## 25 121 152.62 1 0.5761 0.44786
## 26 120 152.18 1 0.4366 0.50876
## 27 119 152.10 1 0.0790 0.77864
## 28 118 150.65 1 1.4530 0.22805
## 29 117 150.58 1 0.0675 0.79506
## 30 116 148.65 1 1.9326 0.16447
## 31 115 130.05 1 18.5980 1.614e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Results
Although the residual deviance reduces with inclusion of more regressors, variance inflation rate (VIF) of the first regressor “overall job satisfaction” shows that duties_variety, job stability and employment status may be unnecessary variables as the VIF increases more with inclusion of these three regressors in the regressor models.
Finally, ANOVA results show “Model: I2L ~ jobsatisfatn + allowances + skillssalary + medsavailable + consumables + protectngear + printedmaterials + workinhrs + quantofwork + workallocatn + divworkinhrs + supportprovided + dutiesvariety + dutiesskills + profrespon + harmonyancteam + recognitncolleague + recognitnbosses + respectbosses + ancselectn4trainin + promotnpport + workquality + profpopularimage + payment_regularity + jobstability + allowanceregularity + workplacereinforcement + decisnmakin + perfinfoanc + employmentstatus” as the model with the highest chisq probability (Pr>1.6 E-05) and thus the best model for predicting the expected value of the outcome - intent to leave work.
Thererfore, from the results, i believe all job satsisfaction variables should be included in the intent to leave regression model.
SELECTED MODEL
##
## Call:
## glm(formula = hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn, family = "binomial")
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.8709 -1.4987 0.8871 0.8871 0.8871
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 1.9743 0.9452 2.089 0.0367 *
## hcp2_f$job_satisfatn -0.4149 0.3353 -1.237 0.2160
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 178.71 on 145 degrees of freedom
## Residual deviance: 177.02 on 144 degrees of freedom
## AIC: 181.02
##
## Number of Fisher Scoring iterations: 4##
## Call:
## glm(formula = hcp2_f$Leave.work - 1 ~ hcp2_f$wkdist + hcp2_f$job_satisfatn,
## family = "binomial")
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.8579 -1.5372 0.8561 0.8561 1.4823
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 3.3956 1.2635 2.688 0.0072 **
## hcp2_f$wkdist -1.5082 0.8902 -1.694 0.0902 .
## hcp2_f$job_satisfatn -0.3575 0.3363 -1.063 0.2878
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 178.71 on 145 degrees of freedom
## Residual deviance: 173.92 on 143 degrees of freedom
## AIC: 179.92
##
## Number of Fisher Scoring iterations: 4## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred##
## Call:
## glm(formula = hcp2_f$Leave.work - 1 ~ hcp2_f$wkdist + hcp2_f$job_satisfatn +
## hcp2_f$allowances + hcp2_f$skills_salary + hcp2_f$meds_available +
## hcp2_f$consumables + hcp2_f$protectn_gear + hcp2_f$printed_materials +
## hcp2_f$workin_hrs + hcp2_f$quant_of_work + hcp2_f$work_allocatn +
## hcp2_f$div_workin_hrs + hcp2_f$support_provided + hcp2_f$duties_skills +
## hcp2_f$prof_respon + hcp2_f$harmony_anc_team + hcp2_f$recognitn_colleague +
## hcp2_f$recognitn_bosses + hcp2_f$respect_bosses + hcp2_f$anc_selectn_4trainin +
## hcp2_f$promotn_opport + hcp2_f$work_quality + hcp2_f$prof_popular_image +
## hcp2_f$payment_regularity + hcp2_f$allowance_regularity +
## hcp2_f$workplace_reinforcement + hcp2_f$decisn_makin + hcp2_f$perf_info_anc,
## family = "binomial")
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.2725 -1.0317 0.5275 0.8798 1.7744
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 4.950e+01 4.454e+03 0.011 0.991
## hcp2_f$wkdist -1.099e+00 9.799e-01 -1.122 0.262
## hcp2_f$job_satisfatn 1.033e-01 4.999e-01 0.207 0.836
## hcp2_f$allowances 2.575e-01 3.154e-01 0.817 0.414
## hcp2_f$skills_salary -4.895e-01 3.222e-01 -1.520 0.129
## hcp2_f$meds_available -7.491e-01 5.108e-01 -1.466 0.143
## hcp2_f$consumables 5.651e-01 4.585e-01 1.232 0.218
## hcp2_f$protectn_gear -1.107e-01 3.260e-01 -0.339 0.734
## hcp2_f$printed_materials 4.113e-01 4.388e-01 0.937 0.349
## hcp2_f$workin_hrs -2.717e-01 5.617e-01 -0.484 0.629
## hcp2_f$quant_of_work 1.953e-01 5.449e-01 0.359 0.720
## hcp2_f$work_allocatn -1.648e-01 5.511e-01 -0.299 0.765
## hcp2_f$div_workin_hrs -6.891e-03 5.282e-01 -0.013 0.990
## hcp2_f$support_provided -1.149e+00 9.851e-01 -1.166 0.244
## hcp2_f$duties_skills 4.968e-02 8.374e-01 0.059 0.953
## hcp2_f$prof_respon 5.951e-01 7.282e-01 0.817 0.414
## hcp2_f$harmony_anc_team 6.451e-01 9.787e-01 0.659 0.510
## hcp2_f$recognitn_colleague 7.495e-01 1.560e+00 0.480 0.631
## hcp2_f$recognitn_bosses -2.257e-01 8.204e-01 -0.275 0.783
## hcp2_f$respect_bosses -1.571e+01 1.485e+03 -0.011 0.992
## hcp2_f$anc_selectn_4trainin -1.450e-01 3.256e-01 -0.445 0.656
## hcp2_f$promotn_opport -6.268e-01 5.229e-01 -1.199 0.231
## hcp2_f$work_quality 5.792e-01 1.051e+00 0.551 0.582
## hcp2_f$prof_popular_image 1.240e+00 1.955e+00 0.634 0.526
## hcp2_f$payment_regularity 1.280e-01 3.428e-01 0.373 0.709
## hcp2_f$allowance_regularity 1.683e-01 3.296e-01 0.511 0.610
## hcp2_f$workplace_reinforcement -3.358e-01 4.892e-01 -0.686 0.492
## hcp2_f$decisn_makin 3.476e-01 5.673e-01 0.613 0.540
## hcp2_f$perf_info_anc -1.328e+00 9.729e-01 -1.365 0.172
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 178.71 on 145 degrees of freedom
## Residual deviance: 151.56 on 117 degrees of freedom
## AIC: 209.56
##
## Number of Fisher Scoring iterations: 17## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred##
## Call:
## glm(formula = hcp2_f$Leave.work - 1 ~ hcp2_f$wkdist + hcp2_f$job_satisfatn +
## hcp2_f$allowances + hcp2_f$skills_salary + hcp2_f$meds_available +
## hcp2_f$consumables + hcp2_f$protectn_gear + hcp2_f$printed_materials +
## hcp2_f$workin_hrs + hcp2_f$quant_of_work + hcp2_f$work_allocatn +
## hcp2_f$div_workin_hrs + hcp2_f$support_provided + hcp2_f$duties_skills +
## hcp2_f$prof_respon + hcp2_f$harmony_anc_team + hcp2_f$recognitn_colleague +
## hcp2_f$recognitn_bosses + hcp2_f$respect_bosses + hcp2_f$anc_selectn_4trainin +
## hcp2_f$promotn_opport + hcp2_f$work_quality + hcp2_f$prof_popular_image +
## hcp2_f$payment_regularity + hcp2_f$allowance_regularity +
## hcp2_f$workplace_reinforcement + hcp2_f$decisn_makin + hcp2_f$perf_info_anc +
## hcp2_f$duties_variety, family = "binomial")
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.4747 -0.9645 0.4732 0.8724 1.6654
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 46.59933 4380.49997 0.011 0.9915
## hcp2_f$wkdist -1.08818 0.97599 -1.115 0.2649
## hcp2_f$job_satisfatn -0.04913 0.52260 -0.094 0.9251
## hcp2_f$allowances 0.22312 0.32175 0.693 0.4880
## hcp2_f$skills_salary -0.41468 0.33464 -1.239 0.2153
## hcp2_f$meds_available -0.71526 0.52649 -1.359 0.1743
## hcp2_f$consumables 0.50629 0.46616 1.086 0.2774
## hcp2_f$protectn_gear -0.13339 0.33812 -0.395 0.6932
## hcp2_f$printed_materials 0.40939 0.45282 0.904 0.3659
## hcp2_f$workin_hrs -0.86790 0.70761 -1.227 0.2200
## hcp2_f$quant_of_work 0.28779 0.59284 0.485 0.6274
## hcp2_f$work_allocatn -0.44609 0.62892 -0.709 0.4781
## hcp2_f$div_workin_hrs -0.29957 0.58960 -0.508 0.6114
## hcp2_f$support_provided -1.46613 1.05352 -1.392 0.1640
## hcp2_f$duties_skills -0.28959 0.86981 -0.333 0.7392
## hcp2_f$prof_respon 0.87031 0.77159 1.128 0.2593
## hcp2_f$harmony_anc_team 0.32650 0.99904 0.327 0.7438
## hcp2_f$recognitn_colleague 1.00052 1.51956 0.658 0.5103
## hcp2_f$recognitn_bosses -0.14451 0.80502 -0.180 0.8575
## hcp2_f$respect_bosses -15.33400 1460.16547 -0.011 0.9916
## hcp2_f$anc_selectn_4trainin -0.13383 0.33166 -0.404 0.6866
## hcp2_f$promotn_opport -0.68422 0.56156 -1.218 0.2231
## hcp2_f$work_quality 0.72589 1.07725 0.674 0.5004
## hcp2_f$prof_popular_image 1.72302 2.03190 0.848 0.3964
## hcp2_f$payment_regularity 0.17768 0.36048 0.493 0.6221
## hcp2_f$allowance_regularity 0.17151 0.34389 0.499 0.6180
## hcp2_f$workplace_reinforcement -0.34293 0.51253 -0.669 0.5034
## hcp2_f$decisn_makin 0.09886 0.59652 0.166 0.8684
## hcp2_f$perf_info_anc -1.32286 1.01054 -1.309 0.1905
## hcp2_f$duties_variety 2.02798 1.06618 1.902 0.0572 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 178.71 on 145 degrees of freedom
## Residual deviance: 147.43 on 116 degrees of freedom
## AIC: 207.43
##
## Number of Fisher Scoring iterations: 17## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred##
## Call:
## glm(formula = hcp2_f$Leave.work - 1 ~ hcp2_f$wkdist + hcp2_f$job_satisfatn +
## hcp2_f$allowances + hcp2_f$skills_salary + hcp2_f$meds_available +
## hcp2_f$consumables + hcp2_f$protectn_gear + hcp2_f$printed_materials +
## hcp2_f$workin_hrs + hcp2_f$quant_of_work + hcp2_f$work_allocatn +
## hcp2_f$div_workin_hrs + hcp2_f$support_provided + hcp2_f$duties_skills +
## hcp2_f$prof_respon + hcp2_f$harmony_anc_team + hcp2_f$recognitn_colleague +
## hcp2_f$recognitn_bosses + hcp2_f$respect_bosses + hcp2_f$anc_selectn_4trainin +
## hcp2_f$promotn_opport + hcp2_f$work_quality + hcp2_f$prof_popular_image +
## hcp2_f$payment_regularity + hcp2_f$allowance_regularity +
## hcp2_f$workplace_reinforcement + hcp2_f$decisn_makin + hcp2_f$perf_info_anc +
## hcp2_f$duties_variety + hcp2_f$employment_status, family = "binomial")
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.83577 -0.79973 0.00035 0.80524 1.77499
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 1.144e+02 1.115e+04 0.010 0.9918
## hcp2_f$wkdist -1.340e+00 9.994e-01 -1.341 0.1799
## hcp2_f$job_satisfatn 1.800e-01 6.464e-01 0.279 0.7806
## hcp2_f$allowances 1.122e-01 3.303e-01 0.340 0.7342
## hcp2_f$skills_salary -3.446e-01 3.539e-01 -0.974 0.3301
## hcp2_f$meds_available -8.001e-01 5.280e-01 -1.515 0.1297
## hcp2_f$consumables 1.786e-01 4.846e-01 0.368 0.7125
## hcp2_f$protectn_gear -1.052e-01 3.446e-01 -0.305 0.7601
## hcp2_f$printed_materials 2.900e-01 4.837e-01 0.600 0.5487
## hcp2_f$workin_hrs -6.124e-01 8.049e-01 -0.761 0.4467
## hcp2_f$quant_of_work 7.218e-01 6.711e-01 1.075 0.2822
## hcp2_f$work_allocatn -5.246e-01 6.693e-01 -0.784 0.4332
## hcp2_f$div_workin_hrs -4.024e-01 6.079e-01 -0.662 0.5080
## hcp2_f$support_provided -2.858e+00 1.398e+00 -2.044 0.0409 *
## hcp2_f$duties_skills 1.818e+00 1.423e+00 1.277 0.2014
## hcp2_f$prof_respon -8.689e-01 1.201e+00 -0.724 0.4692
## hcp2_f$harmony_anc_team 1.665e+00 1.317e+00 1.264 0.2061
## hcp2_f$recognitn_colleague 9.549e-01 2.145e+00 0.445 0.6562
## hcp2_f$recognitn_bosses 7.473e-01 1.027e+00 0.727 0.4669
## hcp2_f$respect_bosses -1.926e+01 3.247e+03 -0.006 0.9953
## hcp2_f$anc_selectn_4trainin -1.380e-01 3.527e-01 -0.391 0.6956
## hcp2_f$promotn_opport -6.374e-01 6.266e-01 -1.017 0.3090
## hcp2_f$work_quality 1.979e+00 2.352e+00 0.841 0.4001
## hcp2_f$prof_popular_image 2.004e+01 1.712e+03 0.012 0.9907
## hcp2_f$payment_regularity 1.262e-01 4.038e-01 0.313 0.7546
## hcp2_f$allowance_regularity 4.511e-01 3.718e-01 1.213 0.2250
## hcp2_f$workplace_reinforcement -2.276e-01 5.468e-01 -0.416 0.6772
## hcp2_f$decisn_makin -9.751e-02 6.699e-01 -0.146 0.8843
## hcp2_f$perf_info_anc 7.519e-02 1.974e+00 0.038 0.9696
## hcp2_f$duties_variety 1.571e+00 1.093e+00 1.438 0.1505
## hcp2_f$employment_status -3.457e+01 2.422e+03 -0.014 0.9886
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 178.71 on 145 degrees of freedom
## Residual deviance: 128.50 on 115 degrees of freedom
## AIC: 190.5
##
## Number of Fisher Scoring iterations: 19## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred##
## Call:
## glm(formula = hcp2_f$Leave.work - 1 ~ hcp2_f$wkdist + hcp2_f$job_satisfatn +
## hcp2_f$allowances + hcp2_f$skills_salary + hcp2_f$meds_available +
## hcp2_f$consumables + hcp2_f$protectn_gear + hcp2_f$printed_materials +
## hcp2_f$workin_hrs + hcp2_f$quant_of_work + hcp2_f$work_allocatn +
## hcp2_f$div_workin_hrs + hcp2_f$support_provided + hcp2_f$duties_skills +
## hcp2_f$prof_respon + hcp2_f$harmony_anc_team + hcp2_f$recognitn_colleague +
## hcp2_f$recognitn_bosses + hcp2_f$respect_bosses + hcp2_f$anc_selectn_4trainin +
## hcp2_f$promotn_opport + hcp2_f$work_quality + hcp2_f$prof_popular_image +
## hcp2_f$payment_regularity + hcp2_f$allowance_regularity +
## hcp2_f$workplace_reinforcement + hcp2_f$decisn_makin + hcp2_f$perf_info_anc +
## hcp2_f$duties_variety + hcp2_f$employment_status + hcp2_f$job_stability,
## family = "binomial")
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.76909 -0.81595 0.00035 0.80147 1.80083
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 1.137e+02 1.111e+04 0.010 0.9918
## hcp2_f$wkdist -1.363e+00 9.949e-01 -1.370 0.1706
## hcp2_f$job_satisfatn 1.113e-01 6.664e-01 0.167 0.8674
## hcp2_f$allowances 1.103e-01 3.328e-01 0.331 0.7404
## hcp2_f$skills_salary -3.516e-01 3.552e-01 -0.990 0.3222
## hcp2_f$meds_available -7.911e-01 5.283e-01 -1.497 0.1343
## hcp2_f$consumables 2.192e-01 4.869e-01 0.450 0.6525
## hcp2_f$protectn_gear -9.597e-02 3.452e-01 -0.278 0.7810
## hcp2_f$printed_materials 3.095e-01 4.863e-01 0.636 0.5245
## hcp2_f$workin_hrs -5.281e-01 8.183e-01 -0.645 0.5187
## hcp2_f$quant_of_work 7.197e-01 6.764e-01 1.064 0.2874
## hcp2_f$work_allocatn -5.538e-01 6.736e-01 -0.822 0.4110
## hcp2_f$div_workin_hrs -4.013e-01 6.151e-01 -0.652 0.5142
## hcp2_f$support_provided -3.111e+00 1.452e+00 -2.142 0.0322 *
## hcp2_f$duties_skills 1.903e+00 1.433e+00 1.328 0.1843
## hcp2_f$prof_respon -9.000e-01 1.228e+00 -0.733 0.4635
## hcp2_f$harmony_anc_team 1.803e+00 1.350e+00 1.336 0.1817
## hcp2_f$recognitn_colleague 1.067e+00 2.176e+00 0.490 0.6240
## hcp2_f$recognitn_bosses 7.496e-01 1.033e+00 0.726 0.4681
## hcp2_f$respect_bosses -1.929e+01 3.244e+03 -0.006 0.9953
## hcp2_f$anc_selectn_4trainin -1.432e-01 3.505e-01 -0.409 0.6829
## hcp2_f$promotn_opport -6.779e-01 6.317e-01 -1.073 0.2832
## hcp2_f$work_quality 2.038e+00 2.387e+00 0.854 0.3934
## hcp2_f$prof_popular_image 2.005e+01 1.698e+03 0.012 0.9906
## hcp2_f$payment_regularity 1.238e-01 4.054e-01 0.305 0.7601
## hcp2_f$allowance_regularity 4.135e-01 3.775e-01 1.096 0.2733
## hcp2_f$workplace_reinforcement -2.263e-01 5.537e-01 -0.409 0.6827
## hcp2_f$decisn_makin -2.168e-01 6.826e-01 -0.318 0.7508
## hcp2_f$perf_info_anc 2.507e-02 1.996e+00 0.013 0.9900
## hcp2_f$duties_variety 1.559e+00 1.108e+00 1.407 0.1593
## hcp2_f$employment_status -3.459e+01 2.402e+03 -0.014 0.9885
## hcp2_f$job_stability 4.185e-01 6.302e-01 0.664 0.5067
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 178.71 on 145 degrees of freedom
## Residual deviance: 128.06 on 114 degrees of freedom
## AIC: 192.06
##
## Number of Fisher Scoring iterations: 19## Analysis of Deviance Table
##
## Model 1: hcp2_f$Leave.work - 1 ~ 1
## Model 2: hcp2_f$Leave.work - 1 ~ hcp2_f$job_satisfatn
## Model 3: hcp2_f$Leave.work - 1 ~ hcp2_f$wkdist + hcp2_f$job_satisfatn
## Model 4: hcp2_f$Leave.work - 1 ~ hcp2_f$wkdist + hcp2_f$job_satisfatn +
## hcp2_f$allowances + hcp2_f$skills_salary + hcp2_f$meds_available +
## hcp2_f$consumables + hcp2_f$protectn_gear + hcp2_f$printed_materials +
## hcp2_f$workin_hrs + hcp2_f$quant_of_work + hcp2_f$work_allocatn +
## hcp2_f$div_workin_hrs + hcp2_f$support_provided + hcp2_f$duties_skills +
## hcp2_f$prof_respon + hcp2_f$harmony_anc_team + hcp2_f$recognitn_colleague +
## hcp2_f$recognitn_bosses + hcp2_f$respect_bosses + hcp2_f$anc_selectn_4trainin +
## hcp2_f$promotn_opport + hcp2_f$work_quality + hcp2_f$prof_popular_image +
## hcp2_f$payment_regularity + hcp2_f$allowance_regularity +
## hcp2_f$workplace_reinforcement + hcp2_f$decisn_makin + hcp2_f$perf_info_anc
## Model 5: hcp2_f$Leave.work - 1 ~ hcp2_f$wkdist + hcp2_f$job_satisfatn +
## hcp2_f$allowances + hcp2_f$skills_salary + hcp2_f$meds_available +
## hcp2_f$consumables + hcp2_f$protectn_gear + hcp2_f$printed_materials +
## hcp2_f$workin_hrs + hcp2_f$quant_of_work + hcp2_f$work_allocatn +
## hcp2_f$div_workin_hrs + hcp2_f$support_provided + hcp2_f$duties_skills +
## hcp2_f$prof_respon + hcp2_f$harmony_anc_team + hcp2_f$recognitn_colleague +
## hcp2_f$recognitn_bosses + hcp2_f$respect_bosses + hcp2_f$anc_selectn_4trainin +
## hcp2_f$promotn_opport + hcp2_f$work_quality + hcp2_f$prof_popular_image +
## hcp2_f$payment_regularity + hcp2_f$allowance_regularity +
## hcp2_f$workplace_reinforcement + hcp2_f$decisn_makin + hcp2_f$perf_info_anc +
## hcp2_f$duties_variety
## Model 6: hcp2_f$Leave.work - 1 ~ hcp2_f$wkdist + hcp2_f$job_satisfatn +
## hcp2_f$allowances + hcp2_f$skills_salary + hcp2_f$meds_available +
## hcp2_f$consumables + hcp2_f$protectn_gear + hcp2_f$printed_materials +
## hcp2_f$workin_hrs + hcp2_f$quant_of_work + hcp2_f$work_allocatn +
## hcp2_f$div_workin_hrs + hcp2_f$support_provided + hcp2_f$duties_skills +
## hcp2_f$prof_respon + hcp2_f$harmony_anc_team + hcp2_f$recognitn_colleague +
## hcp2_f$recognitn_bosses + hcp2_f$respect_bosses + hcp2_f$anc_selectn_4trainin +
## hcp2_f$promotn_opport + hcp2_f$work_quality + hcp2_f$prof_popular_image +
## hcp2_f$payment_regularity + hcp2_f$allowance_regularity +
## hcp2_f$workplace_reinforcement + hcp2_f$decisn_makin + hcp2_f$perf_info_anc +
## hcp2_f$duties_variety + hcp2_f$employment_status
## Model 7: hcp2_f$Leave.work - 1 ~ hcp2_f$wkdist + hcp2_f$job_satisfatn +
## hcp2_f$allowances + hcp2_f$skills_salary + hcp2_f$meds_available +
## hcp2_f$consumables + hcp2_f$protectn_gear + hcp2_f$printed_materials +
## hcp2_f$workin_hrs + hcp2_f$quant_of_work + hcp2_f$work_allocatn +
## hcp2_f$div_workin_hrs + hcp2_f$support_provided + hcp2_f$duties_skills +
## hcp2_f$prof_respon + hcp2_f$harmony_anc_team + hcp2_f$recognitn_colleague +
## hcp2_f$recognitn_bosses + hcp2_f$respect_bosses + hcp2_f$anc_selectn_4trainin +
## hcp2_f$promotn_opport + hcp2_f$work_quality + hcp2_f$prof_popular_image +
## hcp2_f$payment_regularity + hcp2_f$allowance_regularity +
## hcp2_f$workplace_reinforcement + hcp2_f$decisn_makin + hcp2_f$perf_info_anc +
## hcp2_f$duties_variety + hcp2_f$employment_status + hcp2_f$job_stability
## Resid. Df Resid. Dev Df Deviance Pr(>Chi)
## 1 145 178.71
## 2 144 177.02 1 1.6915 0.19340
## 3 143 173.92 1 3.0941 0.07858 .
## 4 117 151.56 26 22.3693 0.66833
## 5 116 147.43 1 4.1263 0.04222 *
## 6 115 128.50 1 18.9282 1.357e-05 ***
## 7 114 128.06 1 0.4379 0.50814
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1With these results I conclude Model 7 (with predictors: work distance, overall job satisfaction, and all uncorrelated job satisfaction covariates except job stability) as the best prediction model of intent to leave work as it has the highest significant difference from the null model (i.e. model with only the mean as a predictor of the outcome - Intent to Leave work).