Regression Support For
Nuclear
Coding Of
Variables
Age- 3- pre millenial 2- millenial 1- Post millenial
Partisanship- 1- no-partisan 2- Weak Partisan 3- Moderate Partisan 4-
Strong Partisan Party- 1- BjP 2- INC 3- Others
Education- 1- HS 2-
Support For Nuclear
1-4
## Factor w/ 3 levels "1","2","3": 2 1 3 1 1 1 3 1 1 1 ...
## GVIF Df GVIF^(1/(2*Df))
## partisan_index_np 1.318746 1 1.148367
## age_cb_new_1 1.007679 1 1.003832
## p_party_new_1 1.321087 2 1.072094
##
## Call:
## glm(formula = q10 ~ partisan_index_np + age_cb_new_1 + p_party_new_1,
## family = binomial, data = ., weights = weight)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## intercept -1.37538 0.06968 -19.738 < 2e-16 ***
## Partisan_Index 0.33784 0.01968 17.169 < 2e-16 ***
## age -0.15900 0.02630 -6.045 1.50e-09 ***
## BJP 0.32572 0.04658 6.992 2.71e-12 ***
## INC -0.32267 0.06878 -4.691 2.71e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 16575 on 12543 degrees of freedom
## Residual deviance: 15870 on 12539 degrees of freedom
## AIC: 15673
##
## Number of Fisher Scoring iterations: 4
|
Observations
|
12544
|
|
Dependent variable
|
q10
|
|
Type
|
Generalized linear model
|
|
Family
|
binomial
|
|
Link
|
logit
|
|
𝛘²(4)
|
705.06
|
|
Pseudo-R² (Cragg-Uhler)
|
0.07
|
|
Pseudo-R² (McFadden)
|
0.04
|
|
AIC
|
15672.89
|
|
BIC
|
15710.08
|
|
|
exp(Est.)
|
2.5%
|
97.5%
|
z val.
|
p
|
|
intercept
|
0.25
|
0.22
|
0.29
|
-19.74
|
0.00
|
|
Partisan_Index
|
1.40
|
1.35
|
1.46
|
17.17
|
0.00
|
|
age
|
0.85
|
0.81
|
0.90
|
-6.04
|
0.00
|
|
BJP
|
1.39
|
1.26
|
1.52
|
6.99
|
0.00
|
|
INC
|
0.72
|
0.63
|
0.83
|
-4.69
|
0.00
|
|
Standard errors: MLE
|
## GVIF Df GVIF^(1/(2*Df))
## partisan_index_np 1.322867 1 1.150160
## p_party_new_1 1.376056 2 1.083076
## geo_region_in_cb_new 1.044254 1 1.021888
##
## Call:
## glm(formula = q10 ~ partisan_index_np + p_party_new_1 + geo_region_in_cb_new,
## family = binomial, data = ., weights = weight)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## intercept -1.50987 0.05890 -25.633 < 2e-16 ***
## Partisan_Index 0.33763 0.01967 17.164 < 2e-16 ***
## BJP 0.25879 0.04734 5.467 4.58e-08 ***
## INC -0.32801 0.06887 -4.763 1.91e-06 ***
## South and East -0.24020 0.03921 -6.125 9.06e-10 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 16575 on 12543 degrees of freedom
## Residual deviance: 15869 on 12539 degrees of freedom
## AIC: 15681
##
## Number of Fisher Scoring iterations: 4
|
Observations
|
12544
|
|
Dependent variable
|
q10
|
|
Type
|
Generalized linear model
|
|
Family
|
binomial
|
|
Link
|
logit
|
|
𝛘²(4)
|
705.84
|
|
Pseudo-R² (Cragg-Uhler)
|
0.07
|
|
Pseudo-R² (McFadden)
|
0.04
|
|
AIC
|
15680.70
|
|
BIC
|
15717.88
|
|
|
exp(Est.)
|
2.5%
|
97.5%
|
z val.
|
p
|
|
intercept
|
0.22
|
0.20
|
0.25
|
-25.63
|
0.00
|
|
Partisan_Index
|
1.40
|
1.35
|
1.46
|
17.16
|
0.00
|
|
BJP
|
1.30
|
1.18
|
1.42
|
5.47
|
0.00
|
|
INC
|
0.72
|
0.63
|
0.82
|
-4.76
|
0.00
|
|
South and East
|
0.79
|
0.73
|
0.85
|
-6.13
|
0.00
|
|
Standard errors: MLE
|
## GVIF Df GVIF^(1/(2*Df))
## partisan_index_np 1.341989 1 1.158443
## age_cb_new_1 1.008936 1 1.004458
## p_party_new_1 1.566421 2 1.118735
## religion_in_new 1.215547 2 1.050009
##
## Call:
## glm(formula = q10 ~ partisan_index_np + age_cb_new_1 + p_party_new_1 +
## religion_in_new, family = binomial, data = ., weights = weight)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## intercept -1.54111 0.07880 -19.556 < 2e-16 ***
## Partisan_Index 0.34308 0.01994 17.209 < 2e-16 ***
## age -0.16392 0.02642 -6.205 5.48e-10 ***
## BJP 0.16083 0.04889 3.289 0.0010 **
## INC -0.20118 0.07010 -2.870 0.0041 **
## Hindu 0.37343 0.05375 6.948 3.70e-12 ***
## Muslim -0.34085 0.07768 -4.388 1.14e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 16575 on 12543 degrees of freedom
## Residual deviance: 15737 on 12537 degrees of freedom
## AIC: 15552
##
## Number of Fisher Scoring iterations: 4
|
Observations
|
12544
|
|
Dependent variable
|
q10
|
|
Type
|
Generalized linear model
|
|
Family
|
binomial
|
|
Link
|
logit
|
|
𝛘²(6)
|
838.69
|
|
Pseudo-R² (Cragg-Uhler)
|
0.09
|
|
Pseudo-R² (McFadden)
|
0.05
|
|
AIC
|
15551.62
|
|
BIC
|
15603.67
|
|
|
exp(Est.)
|
2.5%
|
97.5%
|
z val.
|
p
|
|
intercept
|
0.21
|
0.18
|
0.25
|
-19.56
|
0.00
|
|
Partisan_Index
|
1.41
|
1.36
|
1.47
|
17.21
|
0.00
|
|
age
|
0.85
|
0.81
|
0.89
|
-6.20
|
0.00
|
|
BJP
|
1.17
|
1.07
|
1.29
|
3.29
|
0.00
|
|
INC
|
0.82
|
0.71
|
0.94
|
-2.87
|
0.00
|
|
Hindu
|
1.45
|
1.31
|
1.61
|
6.95
|
0.00
|
|
Muslim
|
0.71
|
0.61
|
0.83
|
-4.39
|
0.00
|
|
Standard errors: MLE
|
## GVIF Df GVIF^(1/(2*Df))
## age_cb_new_1 1.058754 1 1.028958
## p_party_new_1 1.247573 2 1.056858
## religion_in_new 1.201911 2 1.047052
## hub_dist_1 1.041978 1 1.020773
## sec_in_new 1.072770 1 1.035746
##
## Call:
## glm(formula = q10 ~ age_cb_new_1 + p_party_new_1 + religion_in_new +
## hub_dist_1 + sec_in_new, family = binomial, data = ., weights = weight)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## intercept -0.60767 0.09845 -6.173 6.72e-10 ***
## age -0.14458 0.02831 -5.107 3.27e-07 ***
## BJP 0.53697 0.04590 11.698 < 2e-16 ***
## INC 0.21470 0.07197 2.983 0.00285 **
## Hindu 0.42697 0.05677 7.521 5.44e-14 ***
## Muslim -0.20197 0.08257 -2.446 0.01445 *
## Distance -0.20848 0.03737 -5.580 2.41e-08 ***
## Education -0.00785 0.02574 -0.305 0.76035
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 14700 on 11161 degrees of freedom
## Residual deviance: 14212 on 11154 degrees of freedom
## (1382 observations deleted due to missingness)
## AIC: 14127
##
## Number of Fisher Scoring iterations: 4
|
Observations
|
11162 (1382 missing obs. deleted)
|
|
Dependent variable
|
q10
|
|
Type
|
Generalized linear model
|
|
Family
|
binomial
|
|
Link
|
logit
|
|
𝛘²(7)
|
487.68
|
|
Pseudo-R² (Cragg-Uhler)
|
0.06
|
|
Pseudo-R² (McFadden)
|
0.03
|
|
AIC
|
14126.58
|
|
BIC
|
14185.14
|
|
|
exp(Est.)
|
2.5%
|
97.5%
|
z val.
|
p
|
|
intercept
|
0.54
|
0.45
|
0.66
|
-6.17
|
0.00
|
|
age
|
0.87
|
0.82
|
0.91
|
-5.11
|
0.00
|
|
BJP
|
1.71
|
1.56
|
1.87
|
11.70
|
0.00
|
|
INC
|
1.24
|
1.08
|
1.43
|
2.98
|
0.00
|
|
Hindu
|
1.53
|
1.37
|
1.71
|
7.52
|
0.00
|
|
Muslim
|
0.82
|
0.70
|
0.96
|
-2.45
|
0.01
|
|
Distance
|
0.81
|
0.75
|
0.87
|
-5.58
|
0.00
|
|
Education
|
0.99
|
0.94
|
1.04
|
-0.31
|
0.76
|
|
Standard errors: MLE
|
Support For Nuclear
Combined Results Part-1
##
## Results: Support For Use Of Nuclear
## ===================================================================
## Dependent Variable: Support For Use Of Nuclear
## -------------------------------------------------
## Model 1 Model 2 Model 3 Model 4
## (1) (2) (3) (4)
## -------------------------------------------------------------------
## intercept -1.375*** -1.510*** -1.541*** -0.608***
## (0.070) (0.059) (0.079) (0.098)
##
## Partisan_Index 0.338*** 0.338*** 0.343***
## (0.020) (0.020) (0.020)
##
## age -0.159*** -0.164*** -0.145***
## (0.026) (0.026) (0.028)
##
## BJP 0.326*** 0.259*** 0.161*** 0.537***
## (0.047) (0.047) (0.049) (0.046)
##
## INC -0.323*** -0.328*** -0.201*** 0.215***
## (0.069) (0.069) (0.070) (0.072)
##
## South and East -0.240***
## (0.039)
##
## Hindu 0.373*** 0.427***
## (0.054) (0.057)
##
## Muslim -0.341*** -0.202**
## (0.078) (0.083)
##
## Distance -0.208***
## (0.037)
##
## Education -0.008
## (0.026)
##
## -------------------------------------------------------------------
## Observations 12,544 12,544 12,544 11,162
## Log Likelihood -7,831.446 -7,835.348 -7,768.808 -7,055.290
## Akaike Inf. Crit. 15,672.890 15,680.700 15,551.620 14,126.580
## ===================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01
Support For Nuclear
5-8
## GVIF Df GVIF^(1/(2*Df))
## partisan_index_np 1.347358 1 1.160757
## age_cb_new_1 1.059109 1 1.029130
## p_party_new_1 1.619778 2 1.128142
## religion_in_new 1.220386 2 1.051052
## hub_dist_1 1.044991 1 1.022248
## sec_in_new 1.075913 1 1.037262
##
## Call:
## glm(formula = q10 ~ partisan_index_np + age_cb_new_1 + p_party_new_1 +
## religion_in_new + hub_dist_1 + sec_in_new, family = binomial,
## data = ., weights = weight)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## intercept -1.32918 0.11026 -12.055 < 2e-16 ***
## Partisan_Index 0.34239 0.02134 16.045 < 2e-16 ***
## age -0.15150 0.02869 -5.281 1.28e-07 ***
## BJP 0.11881 0.05266 2.256 0.0241 *
## INC -0.15195 0.07569 -2.007 0.0447 *
## Hindu 0.35384 0.05771 6.131 8.72e-10 ***
## Muslim -0.35265 0.08407 -4.195 2.73e-05 ***
## Distance -0.22356 0.03789 -5.900 3.63e-09 ***
## Education 0.01390 0.02607 0.533 0.5939
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 14700 on 11161 degrees of freedom
## Residual deviance: 13950 on 11153 degrees of freedom
## (1382 observations deleted due to missingness)
## AIC: 13872
##
## Number of Fisher Scoring iterations: 4
|
Observations
|
11162 (1382 missing obs. deleted)
|
|
Dependent variable
|
q10
|
|
Type
|
Generalized linear model
|
|
Family
|
binomial
|
|
Link
|
logit
|
|
𝛘²(8)
|
750.30
|
|
Pseudo-R² (Cragg-Uhler)
|
0.09
|
|
Pseudo-R² (McFadden)
|
0.05
|
|
AIC
|
13872.38
|
|
BIC
|
13938.26
|
|
|
exp(Est.)
|
2.5%
|
97.5%
|
z val.
|
p
|
|
intercept
|
0.26
|
0.21
|
0.33
|
-12.05
|
0.00
|
|
Partisan_Index
|
1.41
|
1.35
|
1.47
|
16.05
|
0.00
|
|
age
|
0.86
|
0.81
|
0.91
|
-5.28
|
0.00
|
|
BJP
|
1.13
|
1.02
|
1.25
|
2.26
|
0.02
|
|
INC
|
0.86
|
0.74
|
1.00
|
-2.01
|
0.04
|
|
Hindu
|
1.42
|
1.27
|
1.60
|
6.13
|
0.00
|
|
Muslim
|
0.70
|
0.60
|
0.83
|
-4.19
|
0.00
|
|
Distance
|
0.80
|
0.74
|
0.86
|
-5.90
|
0.00
|
|
Education
|
1.01
|
0.96
|
1.07
|
0.53
|
0.59
|
|
Standard errors: MLE
|
## GVIF Df GVIF^(1/(2*Df))
## age_cb_new_1 1.061356 1 1.030221
## p_party_new_1 1.253927 2 1.058201
## religion_in_new 1.200149 2 1.046668
## geo_region_in_cb_new 1.046369 1 1.022922
## sec_in_new 1.078856 1 1.038680
## gender 1.010855 1 1.005413
##
## Call:
## glm(formula = q10 ~ age_cb_new_1 + p_party_new_1 + religion_in_new +
## geo_region_in_cb_new + sec_in_new + gender, family = binomial,
## data = ., weights = weight)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## intercept -0.35789 0.10660 -3.357 0.000787 ***
## age -0.15740 0.02678 -5.878 4.14e-09 ***
## BJP 0.51898 0.04344 11.946 < 2e-16 ***
## INC 0.16462 0.06691 2.460 0.013885 *
## Hindu 0.43095 0.05302 8.127 4.39e-16 ***
## Muslim -0.20121 0.07651 -2.630 0.008536 **
## South and East -0.21274 0.03910 -5.442 5.28e-08 ***
## Education -0.03727 0.02405 -1.550 0.121235
## gender -0.19333 0.03807 -5.079 3.80e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 16575 on 12543 degrees of freedom
## Residual deviance: 15979 on 12535 degrees of freedom
## AIC: 15788
##
## Number of Fisher Scoring iterations: 4
|
Observations
|
12544
|
|
Dependent variable
|
q10
|
|
Type
|
Generalized linear model
|
|
Family
|
binomial
|
|
Link
|
logit
|
|
𝛘²(8)
|
596.44
|
|
Pseudo-R² (Cragg-Uhler)
|
0.06
|
|
Pseudo-R² (McFadden)
|
0.04
|
|
AIC
|
15788.20
|
|
BIC
|
15855.13
|
|
|
exp(Est.)
|
2.5%
|
97.5%
|
z val.
|
p
|
|
intercept
|
0.70
|
0.57
|
0.86
|
-3.36
|
0.00
|
|
age
|
0.85
|
0.81
|
0.90
|
-5.88
|
0.00
|
|
BJP
|
1.68
|
1.54
|
1.83
|
11.95
|
0.00
|
|
INC
|
1.18
|
1.03
|
1.34
|
2.46
|
0.01
|
|
Hindu
|
1.54
|
1.39
|
1.71
|
8.13
|
0.00
|
|
Muslim
|
0.82
|
0.70
|
0.95
|
-2.63
|
0.01
|
|
South and East
|
0.81
|
0.75
|
0.87
|
-5.44
|
0.00
|
|
Education
|
0.96
|
0.92
|
1.01
|
-1.55
|
0.12
|
|
gender
|
0.82
|
0.76
|
0.89
|
-5.08
|
0.00
|
|
Standard errors: MLE
|
## GVIF Df GVIF^(1/(2*Df))
## partisan_index_np 1.357496 1 1.165116
## gender 1.015775 1 1.007857
## p_party_new_1 1.628015 2 1.129574
## age_cb_new_1 1.062215 1 1.030638
## religion_in_new 1.218510 2 1.050648
## geo_region_in_cb_new 1.049947 1 1.024669
## sec_in_new 1.083048 1 1.040696
##
## Call:
## glm(formula = q10 ~ partisan_index_np + gender + p_party_new_1 +
## age_cb_new_1 + religion_in_new + geo_region_in_cb_new + sec_in_new,
## family = binomial, data = ., weights = weight)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## intercept -1.15415 0.11829 -9.757 < 2e-16 ***
## Partisan_Index 0.34029 0.02006 16.966 < 2e-16 ***
## gender -0.14531 0.03861 -3.764 0.000167 ***
## BJP 0.10292 0.04980 2.067 0.038777 *
## INC -0.19652 0.07038 -2.792 0.005231 **
## age -0.16517 0.02714 -6.086 1.16e-09 ***
## Hindu 0.36306 0.05387 6.739 1.59e-11 ***
## Muslim -0.34859 0.07789 -4.476 7.62e-06 ***
## South and East -0.23481 0.03961 -5.927 3.08e-09 ***
## Education -0.01249 0.02438 -0.512 0.608408
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 16575 on 12543 degrees of freedom
## Residual deviance: 15686 on 12534 degrees of freedom
## AIC: 15504
##
## Number of Fisher Scoring iterations: 4
|
Observations
|
12544
|
|
Dependent variable
|
q10
|
|
Type
|
Generalized linear model
|
|
Family
|
binomial
|
|
Link
|
logit
|
|
𝛘²(9)
|
889.66
|
|
Pseudo-R² (Cragg-Uhler)
|
0.09
|
|
Pseudo-R² (McFadden)
|
0.05
|
|
AIC
|
15504.22
|
|
BIC
|
15578.59
|
|
|
exp(Est.)
|
2.5%
|
97.5%
|
z val.
|
p
|
|
intercept
|
0.32
|
0.25
|
0.40
|
-9.76
|
0.00
|
|
Partisan_Index
|
1.41
|
1.35
|
1.46
|
16.97
|
0.00
|
|
gender
|
0.86
|
0.80
|
0.93
|
-3.76
|
0.00
|
|
BJP
|
1.11
|
1.01
|
1.22
|
2.07
|
0.04
|
|
INC
|
0.82
|
0.72
|
0.94
|
-2.79
|
0.01
|
|
age
|
0.85
|
0.80
|
0.89
|
-6.09
|
0.00
|
|
Hindu
|
1.44
|
1.29
|
1.60
|
6.74
|
0.00
|
|
Muslim
|
0.71
|
0.61
|
0.82
|
-4.48
|
0.00
|
|
South and East
|
0.79
|
0.73
|
0.85
|
-5.93
|
0.00
|
|
Education
|
0.99
|
0.94
|
1.04
|
-0.51
|
0.61
|
|
Standard errors: MLE
|
## GVIF Df GVIF^(1/(2*Df))
## partisan_index_np 1.357718 1 1.165211
## gender 1.016336 1 1.008135
## p_party_new_1 1.639656 2 1.131588
## age_cb_new_1 1.071692 1 1.035226
## religion_in_new 1.241465 2 1.055562
## geo_region_in_cb_new 1.057027 1 1.028118
## sec_in_new 1.097514 1 1.047623
## caste_in_new 1.091455 1 1.044727
##
## Call:
## glm(formula = q10 ~ partisan_index_np + gender + p_party_new_1 +
## age_cb_new_1 + religion_in_new + geo_region_in_cb_new + sec_in_new +
## caste_in_new, family = binomial, data = ., weights = weight)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## intercept -1.090493 0.125193 -8.710 < 2e-16 ***
## Partisan_Index 0.339399 0.020065 16.915 < 2e-16 ***
## gender -0.146689 0.038621 -3.798 0.000146 ***
## BJP 0.096488 0.049972 1.931 0.053502 .
## INC -0.197869 0.070375 -2.812 0.004929 **
## age -0.169101 0.027262 -6.203 5.55e-10 ***
## Hindu 0.351915 0.054350 6.475 9.48e-11 ***
## Muslim -0.360975 0.078306 -4.610 4.03e-06 ***
## South and East -0.229723 0.039753 -5.779 7.52e-09 ***
## Education -0.008113 0.024542 -0.331 0.740973
## caste -0.027497 0.017817 -1.543 0.122752
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 16575 on 12543 degrees of freedom
## Residual deviance: 15683 on 12533 degrees of freedom
## AIC: 15504
##
## Number of Fisher Scoring iterations: 4
|
Observations
|
12544
|
|
Dependent variable
|
q10
|
|
Type
|
Generalized linear model
|
|
Family
|
binomial
|
|
Link
|
logit
|
|
𝛘²(10)
|
892.06
|
|
Pseudo-R² (Cragg-Uhler)
|
0.09
|
|
Pseudo-R² (McFadden)
|
0.05
|
|
AIC
|
15504.44
|
|
BIC
|
15586.25
|
|
|
exp(Est.)
|
2.5%
|
97.5%
|
z val.
|
p
|
|
intercept
|
0.34
|
0.26
|
0.43
|
-8.71
|
0.00
|
|
Partisan_Index
|
1.40
|
1.35
|
1.46
|
16.92
|
0.00
|
|
gender
|
0.86
|
0.80
|
0.93
|
-3.80
|
0.00
|
|
BJP
|
1.10
|
1.00
|
1.21
|
1.93
|
0.05
|
|
INC
|
0.82
|
0.71
|
0.94
|
-2.81
|
0.00
|
|
age
|
0.84
|
0.80
|
0.89
|
-6.20
|
0.00
|
|
Hindu
|
1.42
|
1.28
|
1.58
|
6.47
|
0.00
|
|
Muslim
|
0.70
|
0.60
|
0.81
|
-4.61
|
0.00
|
|
South and East
|
0.79
|
0.74
|
0.86
|
-5.78
|
0.00
|
|
Education
|
0.99
|
0.95
|
1.04
|
-0.33
|
0.74
|
|
caste
|
0.97
|
0.94
|
1.01
|
-1.54
|
0.12
|
|
Standard errors: MLE
|
Combined Support For
Nuclear 5-8
##
## Results: Support For Use Of Nuclear
## =================================
## Statistic N Mean St. Dev. Min Max
## =================================
##
## Results: Support For Use Of Nuclear
## ===================================================================
## Dependent Variable: Support For Use Of Nuclear
## -------------------------------------------------
## Model 5 Model 6 Model 7 Model 8
## (1) (2) (3) (4)
## -------------------------------------------------------------------
## intercept -1.329*** -0.358*** -1.154*** -1.090***
## (0.110) (0.107) (0.118) (0.125)
##
## Partisan_Index 0.342*** 0.340*** 0.339***
## (0.021) (0.020) (0.020)
##
## age -0.152*** -0.157*** -0.165*** -0.169***
## (0.029) (0.027) (0.027) (0.027)
##
## BJP 0.119** 0.519*** 0.103** 0.096*
## (0.053) (0.043) (0.050) (0.050)
##
## INC -0.152** 0.165** -0.197*** -0.198***
## (0.076) (0.067) (0.070) (0.070)
##
## Hindu 0.354*** 0.431*** 0.363*** 0.352***
## (0.058) (0.053) (0.054) (0.054)
##
## Muslim -0.353*** -0.201*** -0.349*** -0.361***
## (0.084) (0.077) (0.078) (0.078)
##
## Distance -0.224***
## (0.038)
##
## South and East -0.213*** -0.235*** -0.230***
## (0.039) (0.040) (0.040)
##
## Education 0.014 -0.037 -0.012 -0.008
## (0.026) (0.024) (0.024) (0.025)
##
## caste -0.027
## (0.018)
##
## gender -0.193*** -0.145*** -0.147***
## (0.038) (0.039) (0.039)
##
## -------------------------------------------------------------------
## Observations 11,162 12,544 12,544 12,544
## Log Likelihood -6,927.191 -7,885.099 -7,742.112 -7,741.220
## Akaike Inf. Crit. 13,872.380 15,788.200 15,504.220 15,504.440
## ===================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01
support For Nuclear
If 50% Chance
## GVIF Df GVIF^(1/(2*Df))
## partisan_index_np 1.368634 1 1.169886
## age_cb_new_1 1.002383 1 1.001191
## p_party_new_1 1.370873 2 1.082055
##
## Call:
## glm(formula = q11a_1 ~ partisan_index_np + age_cb_new_1 + p_party_new_1,
## family = binomial, data = ., weights = weight)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## intercept -0.43869 0.11754 -3.732 0.00019 ***
## Partisan_Index 0.18772 0.03270 5.740 9.48e-09 ***
## age 0.22656 0.04425 5.120 3.05e-07 ***
## BJP 0.13552 0.07792 1.739 0.08199 .
## INC -0.01121 0.11955 -0.094 0.92532
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 6069.1 on 4580 degrees of freedom
## Residual deviance: 5976.0 on 4576 degrees of freedom
## AIC: 5799
##
## Number of Fisher Scoring iterations: 4
|
Observations
|
4581
|
|
Dependent variable
|
q11a_1
|
|
Type
|
Generalized linear model
|
|
Family
|
binomial
|
|
Link
|
logit
|
|
𝛘²(4)
|
93.10
|
|
Pseudo-R² (Cragg-Uhler)
|
0.03
|
|
Pseudo-R² (McFadden)
|
0.02
|
|
AIC
|
5799.04
|
|
BIC
|
5831.19
|
|
|
exp(Est.)
|
2.5%
|
97.5%
|
z val.
|
p
|
|
intercept
|
0.64
|
0.51
|
0.81
|
-3.73
|
0.00
|
|
Partisan_Index
|
1.21
|
1.13
|
1.29
|
5.74
|
0.00
|
|
age
|
1.25
|
1.15
|
1.37
|
5.12
|
0.00
|
|
BJP
|
1.15
|
0.98
|
1.33
|
1.74
|
0.08
|
|
INC
|
0.99
|
0.78
|
1.25
|
-0.09
|
0.93
|
|
Standard errors: MLE
|
## GVIF Df GVIF^(1/(2*Df))
## partisan_index_np 1.372246 1 1.171429
## p_party_new_1 1.412925 2 1.090259
## geo_region_in_cb_new 1.032567 1 1.016153
##
## Call:
## glm(formula = q11a_1 ~ partisan_index_np + p_party_new_1 + geo_region_in_cb_new,
## family = binomial, data = ., weights = weight)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## intercept -0.006686 0.097509 -0.069 0.9453
## Partisan_Index 0.192722 0.032671 5.899 3.66e-09 ***
## BJP 0.122712 0.078639 1.560 0.1187
## INC -0.009799 0.119345 -0.082 0.9346
## South and East -0.151836 0.063828 -2.379 0.0174 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 6069.1 on 4580 degrees of freedom
## Residual deviance: 5996.9 on 4576 degrees of freedom
## AIC: 5822
##
## Number of Fisher Scoring iterations: 4
|
Observations
|
4581
|
|
Dependent variable
|
q11a_1
|
|
Type
|
Generalized linear model
|
|
Family
|
binomial
|
|
Link
|
logit
|
|
𝛘²(4)
|
72.15
|
|
Pseudo-R² (Cragg-Uhler)
|
0.02
|
|
Pseudo-R² (McFadden)
|
0.01
|
|
AIC
|
5821.99
|
|
BIC
|
5854.14
|
|
|
exp(Est.)
|
2.5%
|
97.5%
|
z val.
|
p
|
|
intercept
|
0.99
|
0.82
|
1.20
|
-0.07
|
0.95
|
|
Partisan_Index
|
1.21
|
1.14
|
1.29
|
5.90
|
0.00
|
|
BJP
|
1.13
|
0.97
|
1.32
|
1.56
|
0.12
|
|
INC
|
0.99
|
0.78
|
1.25
|
-0.08
|
0.93
|
|
South and East
|
0.86
|
0.76
|
0.97
|
-2.38
|
0.02
|
|
Standard errors: MLE
|
## GVIF Df GVIF^(1/(2*Df))
## partisan_index_np 1.384052 1 1.176457
## age_cb_new_1 1.002395 1 1.001197
## p_party_new_1 1.609872 2 1.126413
## religion_in_new 1.197437 2 1.046076
##
## Call:
## glm(formula = q11a_1 ~ partisan_index_np + age_cb_new_1 + p_party_new_1 +
## religion_in_new, family = binomial, data = ., weights = weight)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## intercept -0.34156 0.13482 -2.533 0.01129 *
## Partisan_Index 0.19869 0.03294 6.032 1.62e-09 ***
## age 0.22606 0.04432 5.101 3.38e-07 ***
## BJP 0.10104 0.08086 1.250 0.21146
## INC 0.03695 0.12150 0.304 0.76104
## Hindu -0.10114 0.09222 -1.097 0.27279
## Muslim -0.46511 0.13673 -3.402 0.00067 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 6069.1 on 4580 degrees of freedom
## Residual deviance: 5963.9 on 4574 degrees of freedom
## AIC: 5791.6
##
## Number of Fisher Scoring iterations: 4
|
Observations
|
4581
|
|
Dependent variable
|
q11a_1
|
|
Type
|
Generalized linear model
|
|
Family
|
binomial
|
|
Link
|
logit
|
|
𝛘²(6)
|
105.11
|
|
Pseudo-R² (Cragg-Uhler)
|
0.03
|
|
Pseudo-R² (McFadden)
|
0.02
|
|
AIC
|
5791.56
|
|
BIC
|
5836.57
|
|
|
exp(Est.)
|
2.5%
|
97.5%
|
z val.
|
p
|
|
intercept
|
0.71
|
0.55
|
0.93
|
-2.53
|
0.01
|
|
Partisan_Index
|
1.22
|
1.14
|
1.30
|
6.03
|
0.00
|
|
age
|
1.25
|
1.15
|
1.37
|
5.10
|
0.00
|
|
BJP
|
1.11
|
0.94
|
1.30
|
1.25
|
0.21
|
|
INC
|
1.04
|
0.82
|
1.32
|
0.30
|
0.76
|
|
Hindu
|
0.90
|
0.75
|
1.08
|
-1.10
|
0.27
|
|
Muslim
|
0.63
|
0.48
|
0.82
|
-3.40
|
0.00
|
|
Standard errors: MLE
|
## GVIF Df GVIF^(1/(2*Df))
## age_cb_new_1 1.048002 1 1.023720
## p_party_new_1 1.233413 2 1.053846
## religion_in_new 1.197747 2 1.046143
## hub_dist_1 1.036361 1 1.018018
## sec_in_new 1.063423 1 1.031224
##
## Call:
## glm(formula = q11a_1 ~ age_cb_new_1 + p_party_new_1 + religion_in_new +
## hub_dist_1 + sec_in_new, family = binomial, data = ., weights = weight)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## intercept 0.24532 0.16403 1.496 0.1348
## age 0.21248 0.04766 4.458 8.27e-06 ***
## BJP 0.29508 0.07494 3.938 8.23e-05 ***
## INC 0.31075 0.12495 2.487 0.0129 *
## Hindu -0.05534 0.09811 -0.564 0.5727
## Muslim -0.37390 0.14589 -2.563 0.0104 *
## Distance -0.07150 0.06250 -1.144 0.2526
## Education -0.02141 0.04139 -0.517 0.6049
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 5438.5 on 4162 degrees of freedom
## Residual deviance: 5382.6 on 4155 degrees of freedom
## AIC: 5254.3
##
## Number of Fisher Scoring iterations: 4
|
Observations
|
4163
|
|
Dependent variable
|
q11a_1
|
|
Type
|
Generalized linear model
|
|
Family
|
binomial
|
|
Link
|
logit
|
|
𝛘²(7)
|
55.83
|
|
Pseudo-R² (Cragg-Uhler)
|
0.02
|
|
Pseudo-R² (McFadden)
|
0.01
|
|
AIC
|
5254.27
|
|
BIC
|
5304.94
|
|
|
exp(Est.)
|
2.5%
|
97.5%
|
z val.
|
p
|
|
intercept
|
1.28
|
0.93
|
1.76
|
1.50
|
0.13
|
|
age
|
1.24
|
1.13
|
1.36
|
4.46
|
0.00
|
|
BJP
|
1.34
|
1.16
|
1.56
|
3.94
|
0.00
|
|
INC
|
1.36
|
1.07
|
1.74
|
2.49
|
0.01
|
|
Hindu
|
0.95
|
0.78
|
1.15
|
-0.56
|
0.57
|
|
Muslim
|
0.69
|
0.52
|
0.92
|
-2.56
|
0.01
|
|
Distance
|
0.93
|
0.82
|
1.05
|
-1.14
|
0.25
|
|
Education
|
0.98
|
0.90
|
1.06
|
-0.52
|
0.60
|
|
Standard errors: MLE
|
## GVIF Df GVIF^(1/(2*Df))
## partisan_index_np 1.380158 1 1.174801
## age_cb_new_1 1.047972 1 1.023705
## p_party_new_1 1.651108 2 1.133558
## religion_in_new 1.212652 2 1.049383
## hub_dist_1 1.036690 1 1.018180
## sec_in_new 1.067406 1 1.033153
##
## Call:
## glm(formula = q11a_1 ~ partisan_index_np + age_cb_new_1 + p_party_new_1 +
## religion_in_new + hub_dist_1 + sec_in_new, family = binomial,
## data = ., weights = weight)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## intercept -0.244904 0.184625 -1.326 0.18468
## Partisan_Index 0.204356 0.035196 5.806 6.39e-09 ***
## age 0.213515 0.047822 4.465 8.02e-06 ***
## BJP 0.055021 0.086477 0.636 0.52461
## INC 0.091866 0.131187 0.700 0.48376
## Hindu -0.080567 0.098802 -0.815 0.41482
## Muslim -0.455287 0.147446 -3.088 0.00202 **
## Distance -0.077026 0.062807 -1.226 0.22005
## Education -0.007322 0.041667 -0.176 0.86051
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 5438.5 on 4162 degrees of freedom
## Residual deviance: 5348.7 on 4154 degrees of freedom
## (418 observations deleted due to missingness)
## AIC: 5230.8
##
## Number of Fisher Scoring iterations: 4
|
Observations
|
4163 (418 missing obs. deleted)
|
|
Dependent variable
|
q11a_1
|
|
Type
|
Generalized linear model
|
|
Family
|
binomial
|
|
Link
|
logit
|
|
𝛘²(8)
|
89.73
|
|
Pseudo-R² (Cragg-Uhler)
|
0.03
|
|
Pseudo-R² (McFadden)
|
0.02
|
|
AIC
|
5230.78
|
|
BIC
|
5287.79
|
|
|
exp(Est.)
|
2.5%
|
97.5%
|
z val.
|
p
|
|
intercept
|
0.78
|
0.55
|
1.12
|
-1.33
|
0.18
|
|
Partisan_Index
|
1.23
|
1.14
|
1.31
|
5.81
|
0.00
|
|
age
|
1.24
|
1.13
|
1.36
|
4.46
|
0.00
|
|
BJP
|
1.06
|
0.89
|
1.25
|
0.64
|
0.52
|
|
INC
|
1.10
|
0.85
|
1.42
|
0.70
|
0.48
|
|
Hindu
|
0.92
|
0.76
|
1.12
|
-0.82
|
0.41
|
|
Muslim
|
0.63
|
0.48
|
0.85
|
-3.09
|
0.00
|
|
Distance
|
0.93
|
0.82
|
1.05
|
-1.23
|
0.22
|
|
Education
|
0.99
|
0.91
|
1.08
|
-0.18
|
0.86
|
|
Standard errors: MLE
|
## GVIF Df GVIF^(1/(2*Df))
## age_cb_new_1 1.052135 1 1.025736
## p_party_new_1 1.229444 2 1.052997
## religion_in_new 1.187962 2 1.044000
## geo_region_in_cb_new 1.035740 1 1.017713
## sec_in_new 1.070083 1 1.034448
## gender 1.011260 1 1.005614
##
## Call:
## glm(formula = q11a_1 ~ age_cb_new_1 + p_party_new_1 + religion_in_new +
## geo_region_in_cb_new + sec_in_new + gender, family = binomial,
## data = ., weights = weight)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## intercept 0.75032 0.17509 4.285 1.82e-05 ***
## age 0.23246 0.04547 5.112 3.19e-07 ***
## BJP 0.29398 0.07082 4.151 3.31e-05 ***
## INC 0.25398 0.11644 2.181 0.02916 *
## Hindu -0.08438 0.09211 -0.916 0.35962
## Muslim -0.37897 0.13595 -2.788 0.00531 **
## South and East -0.13601 0.06414 -2.121 0.03396 *
## Education -0.04450 0.03905 -1.139 0.25450
## Gender -0.33453 0.06237 -5.364 8.16e-08 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 6069.1 on 4580 degrees of freedom
## Residual deviance: 5966.6 on 4572 degrees of freedom
## AIC: 5784.7
##
## Number of Fisher Scoring iterations: 4
|
Observations
|
4581
|
|
Dependent variable
|
q11a_1
|
|
Type
|
Generalized linear model
|
|
Family
|
binomial
|
|
Link
|
logit
|
|
𝛘²(8)
|
102.43
|
|
Pseudo-R² (Cragg-Uhler)
|
0.03
|
|
Pseudo-R² (McFadden)
|
0.02
|
|
AIC
|
5784.69
|
|
BIC
|
5842.56
|
|
|
exp(Est.)
|
2.5%
|
97.5%
|
z val.
|
p
|
|
intercept
|
2.12
|
1.50
|
2.98
|
4.29
|
0.00
|
|
age
|
1.26
|
1.15
|
1.38
|
5.11
|
0.00
|
|
BJP
|
1.34
|
1.17
|
1.54
|
4.15
|
0.00
|
|
INC
|
1.29
|
1.03
|
1.62
|
2.18
|
0.03
|
|
Hindu
|
0.92
|
0.77
|
1.10
|
-0.92
|
0.36
|
|
Muslim
|
0.68
|
0.52
|
0.89
|
-2.79
|
0.01
|
|
South and East
|
0.87
|
0.77
|
0.99
|
-2.12
|
0.03
|
|
Education
|
0.96
|
0.89
|
1.03
|
-1.14
|
0.25
|
|
Gender
|
0.72
|
0.63
|
0.81
|
-5.36
|
0.00
|
|
Standard errors: MLE
|
## GVIF Df GVIF^(1/(2*Df))
## partisan_index_np 1.395719 1 1.181405
## gender 1.014748 1 1.007347
## p_party_new_1 1.657464 2 1.134648
## age_cb_new_1 1.051951 1 1.025647
## religion_in_new 1.202856 2 1.047257
## geo_region_in_cb_new 1.037471 1 1.018563
## sec_in_new 1.074779 1 1.036715
##
## Call:
## glm(formula = q11a_1 ~ partisan_index_np + gender + p_party_new_1 +
## age_cb_new_1 + religion_in_new + geo_region_in_cb_new + sec_in_new,
## family = binomial, data = ., weights = weight)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## intercept 0.26261 0.19472 1.349 0.177440
## Partisan_Index 0.18970 0.03321 5.713 1.11e-08 ***
## gender -0.31047 0.06271 -4.951 7.39e-07 ***
## BJP 0.06636 0.08199 0.809 0.418294
## INC 0.05463 0.12216 0.447 0.654751
## age 0.23177 0.04560 5.083 3.71e-07 ***
## Hindu -0.10477 0.09265 -1.131 0.258142
## Muslim -0.45556 0.13733 -3.317 0.000909 ***
## South and East -0.15097 0.06443 -2.343 0.019116 *
## Education -0.02947 0.03930 -0.750 0.453362
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 6069.1 on 4580 degrees of freedom
## Residual deviance: 5933.8 on 4571 degrees of freedom
## AIC: 5762.5
##
## Number of Fisher Scoring iterations: 4
|
Observations
|
4581
|
|
Dependent variable
|
q11a_1
|
|
Type
|
Generalized linear model
|
|
Family
|
binomial
|
|
Link
|
logit
|
|
𝛘²(9)
|
135.23
|
|
Pseudo-R² (Cragg-Uhler)
|
0.04
|
|
Pseudo-R² (McFadden)
|
0.02
|
|
AIC
|
5762.53
|
|
BIC
|
5826.83
|
|
|
exp(Est.)
|
2.5%
|
97.5%
|
z val.
|
p
|
|
intercept
|
1.30
|
0.89
|
1.90
|
1.35
|
0.18
|
|
Partisan_Index
|
1.21
|
1.13
|
1.29
|
5.71
|
0.00
|
|
gender
|
0.73
|
0.65
|
0.83
|
-4.95
|
0.00
|
|
BJP
|
1.07
|
0.91
|
1.25
|
0.81
|
0.42
|
|
INC
|
1.06
|
0.83
|
1.34
|
0.45
|
0.65
|
|
age
|
1.26
|
1.15
|
1.38
|
5.08
|
0.00
|
|
Hindu
|
0.90
|
0.75
|
1.08
|
-1.13
|
0.26
|
|
Muslim
|
0.63
|
0.48
|
0.83
|
-3.32
|
0.00
|
|
South and East
|
0.86
|
0.76
|
0.98
|
-2.34
|
0.02
|
|
Education
|
0.97
|
0.90
|
1.05
|
-0.75
|
0.45
|
|
Standard errors: MLE
|
## GVIF Df GVIF^(1/(2*Df))
## partisan_index_np 1.397676 1 1.182233
## gender 1.015201 1 1.007572
## p_party_new_1 1.664525 2 1.135854
## age_cb_new_1 1.058621 1 1.028893
## religion_in_new 1.224201 2 1.051873
## geo_region_in_cb_new 1.044788 1 1.022149
## sec_in_new 1.085777 1 1.042006
## caste_in_new 1.076098 1 1.037352
##
## Call:
## glm(formula = q11a_1 ~ partisan_index_np + gender + p_party_new_1 +
## age_cb_new_1 + religion_in_new + geo_region_in_cb_new + sec_in_new +
## caste_in_new, family = binomial, data = ., weights = weight)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## intercept 0.32405 0.20613 1.572 0.11593
## Partisan_Index 0.18853 0.03323 5.673 1.40e-08 ***
## gender -0.31160 0.06273 -4.967 6.79e-07 ***
## BJP 0.06193 0.08213 0.754 0.45083
## INC 0.05549 0.12216 0.454 0.64967
## age 0.22842 0.04575 4.992 5.96e-07 ***
## Hindu -0.11563 0.09347 -1.237 0.21606
## Muslim -0.46720 0.13799 -3.386 0.00071 ***
## South and East -0.14600 0.06466 -2.258 0.02395 *
## Education -0.02585 0.03951 -0.654 0.51296
## caste -0.02677 0.02939 -0.911 0.36235
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 6069.1 on 4580 degrees of freedom
## Residual deviance: 5933.0 on 4570 degrees of freedom
## AIC: 5763.6
##
## Number of Fisher Scoring iterations: 4
|
Observations
|
4581
|
|
Dependent variable
|
q11a_1
|
|
Type
|
Generalized linear model
|
|
Family
|
binomial
|
|
Link
|
logit
|
|
𝛘²(10)
|
136.06
|
|
Pseudo-R² (Cragg-Uhler)
|
0.04
|
|
Pseudo-R² (McFadden)
|
0.02
|
|
AIC
|
5763.56
|
|
BIC
|
5834.29
|
|
|
exp(Est.)
|
2.5%
|
97.5%
|
z val.
|
p
|
|
intercept
|
1.38
|
0.92
|
2.07
|
1.57
|
0.12
|
|
Partisan_Index
|
1.21
|
1.13
|
1.29
|
5.67
|
0.00
|
|
gender
|
0.73
|
0.65
|
0.83
|
-4.97
|
0.00
|
|
BJP
|
1.06
|
0.91
|
1.25
|
0.75
|
0.45
|
|
INC
|
1.06
|
0.83
|
1.34
|
0.45
|
0.65
|
|
age
|
1.26
|
1.15
|
1.37
|
4.99
|
0.00
|
|
Hindu
|
0.89
|
0.74
|
1.07
|
-1.24
|
0.22
|
|
Muslim
|
0.63
|
0.48
|
0.82
|
-3.39
|
0.00
|
|
South and East
|
0.86
|
0.76
|
0.98
|
-2.26
|
0.02
|
|
Education
|
0.97
|
0.90
|
1.05
|
-0.65
|
0.51
|
|
caste
|
0.97
|
0.92
|
1.03
|
-0.91
|
0.36
|
|
Standard errors: MLE
|
Combined 11a Model
1-4
##
## Results: Support For Use Of Nuclear
## =================================================================================
## Dependent Variable: Support For Use Of Nuclear If 50% Chance
## ---------------------------------------------------------------
## Model 1 Model 2 Model 3 Model 4
## (1) (2) (3) (4)
## ---------------------------------------------------------------------------------
## intercept -0.439*** -0.007 -0.342** 0.245
## (0.118) (0.098) (0.135) (0.164)
##
## Partisan_Index 0.188*** 0.193*** 0.199***
## (0.033) (0.033) (0.033)
##
## age 0.227*** 0.226*** 0.212***
## (0.044) (0.044) (0.048)
##
## BJP 0.136* 0.123 0.101 0.295***
## (0.078) (0.079) (0.081) (0.075)
##
## INC -0.011 -0.010 0.037 0.311**
## (0.120) (0.119) (0.121) (0.125)
##
## South and East -0.152**
## (0.064)
##
## Hindu -0.101 -0.055
## (0.092) (0.098)
##
## Muslim -0.465*** -0.374**
## (0.137) (0.146)
##
## Distance -0.072
## (0.063)
##
## Education -0.021
## (0.041)
##
## ---------------------------------------------------------------------------------
## Observations 4,581 4,581 4,581 4,163
## Log Likelihood -2,894.521 -2,905.995 -2,888.779 -2,619.134
## Akaike Inf. Crit. 5,799.041 5,821.990 5,791.558 5,254.267
## =================================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01
Combined 11a Model
5-8
##
## Results: Support For Use Of Nuclear If 50% Chance Of Retaliation
## =================================================================================
## Dependent Variable: Support For Use Of Nuclear If 50% Chance
## ---------------------------------------------------------------
## Model 5 Model 6 Model 7 Model 8
## (1) (2) (3) (4)
## ---------------------------------------------------------------------------------
## intercept -0.245 0.750*** 0.263 0.324
## (0.185) (0.175) (0.195) (0.206)
##
## Partisan_Index 0.204*** 0.190*** 0.189***
## (0.035) (0.033) (0.033)
##
## gender -0.310*** -0.312***
## (0.063) (0.063)
##
## age 0.214*** 0.232*** 0.232*** 0.228***
## (0.048) (0.045) (0.046) (0.046)
##
## BJP 0.055 0.294*** 0.066 0.062
## (0.086) (0.071) (0.082) (0.082)
##
## INC 0.092 0.254** 0.055 0.055
## (0.131) (0.116) (0.122) (0.122)
##
## Hindu -0.081 -0.084 -0.105 -0.116
## (0.099) (0.092) (0.093) (0.093)
##
## Muslim -0.455*** -0.379*** -0.456*** -0.467***
## (0.147) (0.136) (0.137) (0.138)
##
## Distance -0.077
## (0.063)
##
## South and East -0.136** -0.151** -0.146**
## (0.064) (0.064) (0.065)
##
## Education -0.007 -0.044 -0.029 -0.026
## (0.042) (0.039) (0.039) (0.040)
##
## Gender -0.335***
## (0.062)
##
## caste -0.027
## (0.029)
##
## ---------------------------------------------------------------------------------
## Observations 4,163 4,581 4,581 4,581
## Log Likelihood -2,606.390 -2,883.345 -2,871.265 -2,870.781
## Akaike Inf. Crit. 5,230.779 5,784.691 5,762.531 5,763.563
## =================================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01
Partisan Index
Graph
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 1.000 2.000 3.000 2.912 4.000 4.000
## dbl+lbl [1:12544] 3, 1, 3, 1, 1, 2, 1, 3, 3, 2, 2, 4, 3, 3, 4, 2, 1, 2, 3,...
## @ label : chr "When comparing the performance of Narendra Modi's first term (2014-2019) with his second term (since 2019), how"| __truncated__
## @ format.spss: chr "F1.0"
## @ labels : Named num [1:5] 1 2 3 4 5
## ..- attr(*, "names")= chr [1:5] "The first term was better than the second one" "The second term was better that the first one" "Both terms were equally good" "Both terms were equally bad" ...
##
## Call:
## glm(formula = q10 ~ partisan_index_party, family = "binomial",
## data = mint11_df_1_1)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -0.94883 0.02687 -35.32 <2e-16 ***
## partisan_index_party 0.22757 0.01042 21.83 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 16466 on 12543 degrees of freedom
## Residual deviance: 15981 on 12542 degrees of freedom
## AIC: 15985
##
## Number of Fisher Scoring iterations: 4
##
## Call:
## glm(formula = q10 ~ partisan_index_party, family = "binomial",
## data = mint11_df_1_2)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -0.52227 0.01959 -26.659 < 2e-16 ***
## partisan_index_party -0.08247 0.01765 -4.673 2.97e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 16466 on 12543 degrees of freedom
## Residual deviance: 16444 on 12542 degrees of freedom
## AIC: 16448
##
## Number of Fisher Scoring iterations: 4
##
## Call:
## glm(formula = q10 ~ partisan_index_party, family = "binomial",
## data = mint11_df_1_3)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -0.54064 0.02061 -26.227 <2e-16 ***
## partisan_index_party -0.01827 0.01352 -1.351 0.177
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 16466 on 12543 degrees of freedom
## Residual deviance: 16465 on 12542 degrees of freedom
## AIC: 16469
##
## Number of Fisher Scoring iterations: 4
##
## Call:
## glm(formula = q10 ~ partisan_index_party, family = "binomial",
## data = mint11_df_1_3)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -0.54064 0.02061 -26.227 <2e-16 ***
## partisan_index_party -0.01827 0.01352 -1.351 0.177
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 16466 on 12543 degrees of freedom
## Residual deviance: 16465 on 12542 degrees of freedom
## AIC: 16469
##
## Number of Fisher Scoring iterations: 4
