Overall
Regression test result at national level
## [1] "Predicotr variable:food_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -48945 -1284 -322 337 232748
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.019e+03 3.139e+01 159.88 <2e-16 ***
## df[[vars$outcome[i]]] 5.675e-03 3.444e-04 16.48 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 4814 on 38055 degrees of freedom
## (13866 observations deleted due to missingness)
## Multiple R-squared: 0.007085, Adjusted R-squared: 0.007059
## F-statistic: 271.6 on 1 and 38055 DF, p-value: < 2.2e-16
##
## [1] "p-value: 0.000344403220735016"
## [1] "TEST RESULT: Ho rejects"
## [1] "Predicotr variable:water_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -1603 -127 -50 -5 32357
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.388e+02 2.619e+00 53.001 < 2e-16 ***
## df[[vars$outcome[i]]] 1.214e-04 2.873e-05 4.225 2.39e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 401.9 on 38075 degrees of freedom
## (13846 observations deleted due to missingness)
## Multiple R-squared: 0.0004687, Adjusted R-squared: 0.0004424
## F-statistic: 17.85 on 1 and 38075 DF, p-value: 2.391e-05
##
## [1] "p-value: 2.87330282961671e-05"
## [1] "TEST RESULT: Ho rejects"
## [1] "Predicotr variable:rent_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -9405 -548 -158 215 105993
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 7.314e+02 1.143e+01 64.01 < 2e-16 ***
## df[[vars$outcome[i]]] 9.201e-04 1.255e-04 7.33 2.35e-13 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1750 on 37967 degrees of freedom
## (13954 observations deleted due to missingness)
## Multiple R-squared: 0.001413, Adjusted R-squared: 0.001387
## F-statistic: 53.73 on 1 and 37967 DF, p-value: 2.346e-13
##
## [1] "p-value: 0.000125521568620494"
## [1] "TEST RESULT: Ho rejects"
## [1] "Predicotr variable:health_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -16514 -1021 -357 18 122642
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.918e+03 4.016e+01 47.75 <2e-16 ***
## df[[vars$outcome[i]]] 1.160e-02 5.288e-04 21.94 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 4267 on 18210 degrees of freedom
## (33711 observations deleted due to missingness)
## Multiple R-squared: 0.02576, Adjusted R-squared: 0.0257
## F-statistic: 481.4 on 1 and 18210 DF, p-value: < 2.2e-16
##
## [1] "p-value: 0.000528808863844622"
## [1] "TEST RESULT: Ho rejects"
## [1] "Predicotr variable:transportation_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -4229.7 -276.9 -101.3 92.9 30987.7
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.753e+02 1.930e+01 29.811 < 2e-16 ***
## df[[vars$outcome[i]]] 2.029e-03 2.632e-04 7.707 1.46e-14 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1180 on 7192 degrees of freedom
## (44729 observations deleted due to missingness)
## Multiple R-squared: 0.008191, Adjusted R-squared: 0.008053
## F-statistic: 59.4 on 1 and 7192 DF, p-value: 1.461e-14
##
## [1] "p-value: 0.000263225631564699"
## [1] "TEST RESULT: Ho rejects"
## [1] "Predicotr variable:education_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -1272.4 -171.8 -79.0 -33.0 24561.8
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.035e+02 9.796e+00 20.773 < 2e-16 ***
## df[[vars$outcome[i]]] 7.929e-04 1.337e-04 5.931 3.15e-09 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 599 on 7192 degrees of freedom
## (44729 observations deleted due to missingness)
## Multiple R-squared: 0.004868, Adjusted R-squared: 0.004729
## F-statistic: 35.18 on 1 and 7192 DF, p-value: 3.145e-09
##
## [1] "p-value: 0.00013368172769653"
## [1] "TEST RESULT: Ho rejects"
## [1] "Predicotr variable:communications_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -1475.8 -103.4 -38.9 33.8 10697.5
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.685e+02 5.885e+00 45.620 <2e-16 ***
## df[[vars$outcome[i]]] 7.082e-04 8.028e-05 8.822 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 359.9 on 7196 degrees of freedom
## (44725 observations deleted due to missingness)
## Multiple R-squared: 0.0107, Adjusted R-squared: 0.01056
## F-statistic: 77.83 on 1 and 7196 DF, p-value: < 2.2e-16
##
## [1] "p-value: 8.02804510491905e-05"
## [1] "TEST RESULT: Ho rejects"
## [1] "Predicotr variable:fuel_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -13604 -378 -77 142 36190
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 8.344e+02 7.037e+00 118.58 <2e-16 ***
## df[[vars$outcome[i]]] 1.890e-03 7.726e-05 24.46 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1079 on 38050 degrees of freedom
## (13871 observations deleted due to missingness)
## Multiple R-squared: 0.01548, Adjusted R-squared: 0.01545
## F-statistic: 598.3 on 1 and 38050 DF, p-value: < 2.2e-16
##
## [1] "p-value: 7.72631012508635e-05"
## [1] "TEST RESULT: Ho rejects"
## [1] "Predicotr variable:debt_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -15149 -735 -332 -133 228361
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.889e+02 3.102e+01 18.985 <2e-16 ***
## df[[vars$outcome[i]]] 2.955e-03 3.405e-04 8.679 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 4760 on 38103 degrees of freedom
## (13818 observations deleted due to missingness)
## Multiple R-squared: 0.001973, Adjusted R-squared: 0.001947
## F-statistic: 75.33 on 1 and 38103 DF, p-value: < 2.2e-16
##
## [1] "p-value: 0.000340481732989287"
## [1] "TEST RESULT: Ho rejects"
By Population
Regression test result by population group
Population group: idps
## [1] "Population group:idps"
## [1] "Predicotr variable:food_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -10662 -843 -167 354 147649
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.529e+03 3.423e+01 132.286 <2e-16 ***
## df[[vars$outcome[i]]] 3.714e-03 4.035e-04 9.204 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2998 on 21213 degrees of freedom
## (6345 observations deleted due to missingness)
## Multiple R-squared: 0.003978, Adjusted R-squared: 0.003931
## F-statistic: 84.72 on 1 and 21213 DF, p-value: < 2.2e-16
##
## [1] "p-value: 0.000403468314720973"
## [1] "TEST RESULT: Ho rejects"
## [1] "Population group:idps"
## [1] "Predicotr variable:water_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -591.9 -88.7 -37.6 16.4 7919.4
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.399e+02 2.873e+00 48.682 <2e-16 ***
## df[[vars$outcome[i]]] 2.923e-04 3.385e-05 8.634 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 251.8 on 21229 degrees of freedom
## (6329 observations deleted due to missingness)
## Multiple R-squared: 0.0035, Adjusted R-squared: 0.003453
## F-statistic: 74.55 on 1 and 21229 DF, p-value: < 2.2e-16
##
## [1] "p-value: 3.38545713968524e-05"
## [1] "TEST RESULT: Ho rejects"
## [1] "Population group:idps"
## [1] "Predicotr variable:rent_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -3221 -424 -74 207 59780
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.008e+03 1.531e+01 65.800 < 2e-16 ***
## df[[vars$outcome[i]]] 7.620e-04 1.809e-04 4.213 2.53e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1339 on 21167 degrees of freedom
## (6391 observations deleted due to missingness)
## Multiple R-squared: 0.0008378, Adjusted R-squared: 0.0007906
## F-statistic: 17.75 on 1 and 21167 DF, p-value: 2.531e-05
##
## [1] "p-value: 0.000180859452262939"
## [1] "TEST RESULT: Ho rejects"
## [1] "Population group:idps"
## [1] "Predicotr variable:health_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -12326 -778 -304 -38 84930
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.183e+03 5.245e+01 41.63 <2e-16 ***
## df[[vars$outcome[i]]] 7.912e-03 7.223e-04 10.95 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 3108 on 11854 degrees of freedom
## (15704 observations deleted due to missingness)
## Multiple R-squared: 0.01002, Adjusted R-squared: 0.009937
## F-statistic: 120 on 1 and 11854 DF, p-value: < 2.2e-16
##
## [1] "p-value: 0.000722283792426694"
## [1] "TEST RESULT: Ho rejects"
## [1] "Population group:idps"
## [1] "Predicotr variable:transportation_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -1170.7 -202.2 -88.4 54.1 10027.6
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.806e+02 2.698e+01 21.519 < 2e-16 ***
## df[[vars$outcome[i]]] 2.364e-03 3.721e-04 6.352 2.31e-10 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 603.1 on 4817 degrees of freedom
## (22741 observations deleted due to missingness)
## Multiple R-squared: 0.008308, Adjusted R-squared: 0.008102
## F-statistic: 40.35 on 1 and 4817 DF, p-value: 2.314e-10
##
## [1] "p-value: 0.000372053543368382"
## [1] "TEST RESULT: Ho rejects"
## [1] "Population group:idps"
## [1] "Predicotr variable:education_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -373.5 -67.0 -39.9 -20.2 6896.7
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.186e+02 1.059e+01 11.207 < 2e-16 ***
## df[[vars$outcome[i]]] 7.274e-04 1.461e-04 4.979 6.63e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 236.6 on 4817 degrees of freedom
## (22741 observations deleted due to missingness)
## Multiple R-squared: 0.005119, Adjusted R-squared: 0.004913
## F-statistic: 24.79 on 1 and 4817 DF, p-value: 6.629e-07
##
## [1] "p-value: 0.000146109416018916"
## [1] "TEST RESULT: Ho rejects"
## [1] "Population group:idps"
## [1] "Predicotr variable:communications_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -389.4 -54.0 -18.7 26.6 4141.0
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.233e+02 6.521e+00 34.248 < 2e-16 ***
## df[[vars$outcome[i]]] 7.106e-04 8.990e-05 7.904 3.32e-15 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 145.8 on 4819 degrees of freedom
## (22739 observations deleted due to missingness)
## Multiple R-squared: 0.0128, Adjusted R-squared: 0.01259
## F-statistic: 62.48 on 1 and 4819 DF, p-value: 3.317e-15
##
## [1] "p-value: 8.98976497153348e-05"
## [1] "TEST RESULT: Ho rejects"
## [1] "Population group:idps"
## [1] "Predicotr variable:fuel_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -2115.5 -171.1 -8.1 173.1 12843.0
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 6.716e+02 7.008e+00 95.828 < 2e-16 ***
## df[[vars$outcome[i]]] 6.023e-04 8.260e-05 7.291 3.17e-13 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 613.8 on 21223 degrees of freedom
## (6335 observations deleted due to missingness)
## Multiple R-squared: 0.002499, Adjusted R-squared: 0.002452
## F-statistic: 53.17 on 1 and 21223 DF, p-value: 3.173e-13
##
## [1] "p-value: 8.25965571068694e-05"
## [1] "TEST RESULT: Ho rejects"
## [1] "Population group:idps"
## [1] "Predicotr variable:debt_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -2624 -505 -262 -105 105959
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 6.399e+02 3.267e+01 19.586 < 2e-16 ***
## df[[vars$outcome[i]]] 1.246e-03 3.850e-04 3.237 0.00121 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2863 on 21242 degrees of freedom
## (6316 observations deleted due to missingness)
## Multiple R-squared: 0.0004931, Adjusted R-squared: 0.0004461
## F-statistic: 10.48 on 1 and 21242 DF, p-value: 0.001208
##
## [1] "p-value: 0.00038499923680882"
## [1] "TEST RESULT: Ho rejects"
Population group: returnees
## [1] "Population group:returnees"
## [1] "Predicotr variable:food_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -16868 -922 -281 442 78862
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.269e+03 7.756e+01 55.04 <2e-16 ***
## df[[vars$outcome[i]]] 1.465e-02 8.555e-04 17.13 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 3089 on 5282 degrees of freedom
## (2396 observations deleted due to missingness)
## Multiple R-squared: 0.05263, Adjusted R-squared: 0.05245
## F-statistic: 293.4 on 1 and 5282 DF, p-value: < 2.2e-16
##
## [1] "p-value: 0.000855493936607985"
## [1] "TEST RESULT: Ho rejects"
## [1] "Population group:returnees"
## [1] "Predicotr variable:water_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -319.0 -81.1 -49.7 -22.9 23624.1
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.455e+02 1.067e+01 13.64 <2e-16 ***
## df[[vars$outcome[i]]] -1.976e-04 1.176e-04 -1.68 0.0929 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 425.7 on 5278 degrees of freedom
## (2400 observations deleted due to missingness)
## Multiple R-squared: 0.0005347, Adjusted R-squared: 0.0003453
## F-statistic: 2.824 on 1 and 5278 DF, p-value: 0.09294
##
## [1] "p-value: 0.000117594510244631"
## [1] "TEST RESULT: Ho rejects"
## [1] "Population group:returnees"
## [1] "Predicotr variable:rent_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -1888 -437 -214 73 34981
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 8.379e+02 3.242e+01 25.845 < 2e-16 ***
## df[[vars$outcome[i]]] -9.475e-04 3.567e-04 -2.656 0.00792 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1290 on 5267 degrees of freedom
## (2411 observations deleted due to missingness)
## Multiple R-squared: 0.001338, Adjusted R-squared: 0.001148
## F-statistic: 7.056 on 1 and 5267 DF, p-value: 0.007923
##
## [1] "p-value: 0.000356683633385711"
## [1] "TEST RESULT: Ho rejects"
## [1] "Population group:returnees"
## [1] "Predicotr variable:health_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -6307 -1305 -675 -26 72961
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.204e+03 1.549e+02 14.228 <2e-16 ***
## df[[vars$outcome[i]]] 5.488e-03 2.332e-03 2.353 0.0188 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 4047 on 1400 degrees of freedom
## (6278 observations deleted due to missingness)
## Multiple R-squared: 0.003939, Adjusted R-squared: 0.003227
## F-statistic: 5.536 on 1 and 1400 DF, p-value: 0.01877
##
## [1] "p-value: 0.00233235019468631"
## [1] "TEST RESULT: Ho rejects"
## [1] "Population group:returnees"
## [1] "Predicotr variable:fuel_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -3179.5 -261.2 2.2 321.0 7879.6
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 7.438e+02 1.547e+01 48.08 <2e-16 ***
## df[[vars$outcome[i]]] 2.814e-03 1.707e-04 16.49 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 616.7 on 5273 degrees of freedom
## (2405 observations deleted due to missingness)
## Multiple R-squared: 0.04902, Adjusted R-squared: 0.04884
## F-statistic: 271.8 on 1 and 5273 DF, p-value: < 2.2e-16
##
## [1] "p-value: 0.000170719016569889"
## [1] "TEST RESULT: Ho rejects"
## [1] "Population group:returnees"
## [1] "Predicotr variable:debt_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -2500 -520 -323 -163 63974
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 6.509e+02 6.401e+01 10.169 <2e-16 ***
## df[[vars$outcome[i]]] 1.539e-03 7.055e-04 2.181 0.0292 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2555 on 5288 degrees of freedom
## (2390 observations deleted due to missingness)
## Multiple R-squared: 0.0008989, Adjusted R-squared: 0.00071
## F-statistic: 4.758 on 1 and 5288 DF, p-value: 0.02921
##
## [1] "p-value: 0.000705549125334165"
## [1] "TEST RESULT: Ho rejects"
Population group: refugees
## [1] "Population group:refugees"
## [1] "Predicotr variable:food_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -6417.1 -675.8 -356.3 365.6 10172.1
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.913e+03 1.507e+02 32.607 <2e-16 ***
## df[[vars$outcome[i]]] 2.355e-03 1.060e-03 2.222 0.0265 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1459 on 962 degrees of freedom
## (95 observations deleted due to missingness)
## Multiple R-squared: 0.005105, Adjusted R-squared: 0.004071
## F-statistic: 4.937 on 1 and 962 DF, p-value: 0.02653
##
## [1] "p-value: 0.00106001578421661"
## [1] "TEST RESULT: Ho rejects"
## [1] "Population group:refugees"
## [1] "Predicotr variable:water_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -1156.84 -103.75 -43.17 -7.16 2278.42
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -4.175e+01 3.604e+01 -1.159 0.247
## df[[vars$outcome[i]]] 2.904e-03 2.536e-04 11.451 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 349.4 on 965 degrees of freedom
## (92 observations deleted due to missingness)
## Multiple R-squared: 0.1196, Adjusted R-squared: 0.1187
## F-statistic: 131.1 on 1 and 965 DF, p-value: < 2.2e-16
##
## [1] "p-value: 0.000253621296773446"
## [1] "TEST RESULT: Ho rejects"
## [1] "Population group:refugees"
## [1] "Predicotr variable:rent_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -3272.8 -367.7 -241.1 433.7 2669.3
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.856e+02 6.896e+01 7.042 3.65e-12 ***
## df[[vars$outcome[i]]] 6.204e-03 4.849e-04 12.794 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 662.9 on 945 degrees of freedom
## (112 observations deleted due to missingness)
## Multiple R-squared: 0.1476, Adjusted R-squared: 0.1467
## F-statistic: 163.7 on 1 and 945 DF, p-value: < 2.2e-16
##
## [1] "p-value: 0.000484931016641191"
## [1] "TEST RESULT: Ho rejects"
## [1] "Population group:refugees"
## [1] "Predicotr variable:health_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -5621 -1496 -1081 -303 118335
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.283e+03 8.319e+02 6.351 5.39e-10 ***
## df[[vars$outcome[i]]] -1.147e-02 6.908e-03 -1.661 0.0975 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6185 on 436 degrees of freedom
## (621 observations deleted due to missingness)
## Multiple R-squared: 0.006286, Adjusted R-squared: 0.004007
## F-statistic: 2.758 on 1 and 436 DF, p-value: 0.09749
##
## [1] "p-value: 0.00690753097200674"
## [1] "TEST RESULT: Ho rejects"
## [1] "Population group:refugees"
## [1] "Predicotr variable:transportation_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -1108.36 -131.15 -1.59 150.53 1704.70
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 7.490e+02 9.480e+01 7.901 3.11e-10 ***
## df[[vars$outcome[i]]] 5.723e-04 7.626e-04 0.750 0.457
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 438.4 on 48 degrees of freedom
## (1009 observations deleted due to missingness)
## Multiple R-squared: 0.01159, Adjusted R-squared: -0.008997
## F-statistic: 0.5631 on 1 and 48 DF, p-value: 0.4567
##
## [1] "p-value: 0.000762640766584675"
## [1] "TEST RESULT: Ho rejects"
## [1] "Population group:refugees"
## [1] "Predicotr variable:education_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -148.56 -83.52 -13.20 -9.65 1110.90
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.107e+02 4.179e+01 2.649 0.0109 *
## df[[vars$outcome[i]]] -5.211e-04 3.362e-04 -1.550 0.1277
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 193.3 on 48 degrees of freedom
## (1009 observations deleted due to missingness)
## Multiple R-squared: 0.04766, Adjusted R-squared: 0.02782
## F-statistic: 2.402 on 1 and 48 DF, p-value: 0.1277
##
## [1] "p-value: 0.000336224185506336"
## [1] "TEST RESULT: Ho rejects"
## [1] "Population group:refugees"
## [1] "Predicotr variable:communications_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -437.20 -23.54 -18.21 29.00 887.99
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.688e+02 3.964e+01 9.304 2.55e-12 ***
## df[[vars$outcome[i]]] -6.909e-04 3.189e-04 -2.167 0.0352 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 183.3 on 48 degrees of freedom
## (1009 observations deleted due to missingness)
## Multiple R-squared: 0.08909, Adjusted R-squared: 0.07012
## F-statistic: 4.695 on 1 and 48 DF, p-value: 0.03525
##
## [1] "p-value: 0.000318879349574019"
## [1] "TEST RESULT: Ho rejects"
## [1] "Population group:refugees"
## [1] "Predicotr variable:fuel_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -2040.78 -276.80 15.45 309.34 2547.26
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 7.810e+02 4.443e+01 17.578 < 2e-16 ***
## df[[vars$outcome[i]]] 2.275e-03 3.128e-04 7.272 7.32e-13 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 431 on 966 degrees of freedom
## (91 observations deleted due to missingness)
## Multiple R-squared: 0.0519, Adjusted R-squared: 0.05092
## F-statistic: 52.88 on 1 and 966 DF, p-value: 7.316e-13
##
## [1] "p-value: 0.000312791581567045"
## [1] "TEST RESULT: Ho rejects"
## [1] "Population group:refugees"
## [1] "Predicotr variable:debt_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -583.3 -161.5 -138.0 -62.5 23008.6
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 432.435153 116.200805 3.721 0.00021 ***
## df[[vars$outcome[i]]] -0.001414 0.000818 -1.728 0.08431 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1127 on 966 degrees of freedom
## (91 observations deleted due to missingness)
## Multiple R-squared: 0.003081, Adjusted R-squared: 0.002049
## F-statistic: 2.986 on 1 and 966 DF, p-value: 0.08431
##
## [1] "p-value: 0.000818042161467335"
## [1] "TEST RESULT: Ho rejects"
Population group: non_displaced
## [1] "Population group:non_displaced"
## [1] "Predicotr variable:food_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -51743 -2433 -597 636 231562
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.404e+03 6.495e+01 83.205 < 2e-16 ***
## df[[vars$outcome[i]]] 5.481e-03 6.904e-04 7.939 2.25e-15 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7711 on 10592 degrees of freedom
## (5030 observations deleted due to missingness)
## Multiple R-squared: 0.005915, Adjusted R-squared: 0.005821
## F-statistic: 63.02 on 1 and 10592 DF, p-value: 2.25e-15
##
## [1] "p-value: 0.000690449984621469"
## [1] "TEST RESULT: Ho rejects"
## [1] "Population group:non_displaced"
## [1] "Predicotr variable:water_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -1295 -194 -122 -19 32361
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.384e+02 4.980e+00 27.796 <2e-16 ***
## df[[vars$outcome[i]]] 3.225e-05 5.294e-05 0.609 0.542
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 591.4 on 10597 degrees of freedom
## (5025 observations deleted due to missingness)
## Multiple R-squared: 3.502e-05, Adjusted R-squared: -5.934e-05
## F-statistic: 0.3711 on 1 and 10597 DF, p-value: 0.5424
##
## [1] "p-value: 5.2942955364646e-05"
## [1] "TEST RESULT: Ho rejects"
## [1] "Population group:non_displaced"
## [1] "Predicotr variable:rent_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -8839 -859 -541 -88 106193
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.608e+02 2.131e+01 26.314 < 2e-16 ***
## df[[vars$outcome[i]]] 1.181e-03 2.269e-04 5.206 1.96e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2528 on 10582 degrees of freedom
## (5040 observations deleted due to missingness)
## Multiple R-squared: 0.002555, Adjusted R-squared: 0.002461
## F-statistic: 27.11 on 1 and 10582 DF, p-value: 1.963e-07
##
## [1] "p-value: 0.000226866669580319"
## [1] "TEST RESULT: Ho rejects"
## [1] "Population group:non_displaced"
## [1] "Predicotr variable:health_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -19656 -1889 -690 692 115678
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.740e+03 7.470e+01 23.29 <2e-16 ***
## df[[vars$outcome[i]]] 1.396e-02 9.570e-04 14.59 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6245 on 4514 degrees of freedom
## (11108 observations deleted due to missingness)
## Multiple R-squared: 0.04502, Adjusted R-squared: 0.04481
## F-statistic: 212.8 on 1 and 4514 DF, p-value: < 2.2e-16
##
## [1] "p-value: 0.000956961948408267"
## [1] "TEST RESULT: Ho rejects"
## [1] "Population group:non_displaced"
## [1] "Predicotr variable:transportation_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -4174.5 -672.0 -234.5 343.0 30996.2
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.728e+02 3.327e+01 17.218 < 2e-16 ***
## df[[vars$outcome[i]]] 2.000e-03 4.560e-04 4.385 1.21e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1884 on 2323 degrees of freedom
## (13299 observations deleted due to missingness)
## Multiple R-squared: 0.008209, Adjusted R-squared: 0.007782
## F-statistic: 19.23 on 1 and 2323 DF, p-value: 1.212e-05
##
## [1] "p-value: 0.000456047946517376"
## [1] "TEST RESULT: Ho rejects"
## [1] "Population group:non_displaced"
## [1] "Predicotr variable:education_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -1357.8 -353.6 -248.1 -1.1 24496.6
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.164e+02 1.756e+01 12.33 < 2e-16 ***
## df[[vars$outcome[i]]] 8.522e-04 2.408e-04 3.54 0.000408 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 994.6 on 2323 degrees of freedom
## (13299 observations deleted due to missingness)
## Multiple R-squared: 0.005365, Adjusted R-squared: 0.004937
## F-statistic: 12.53 on 1 and 2323 DF, p-value: 0.0004085
##
## [1] "p-value: 0.000240762183290723"
## [1] "TEST RESULT: Ho rejects"
## [1] "Population group:non_displaced"
## [1] "Predicotr variable:communications_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -1515.7 -239.8 -101.5 148.9 10681.8
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.744e+02 1.051e+01 26.101 < 2e-16 ***
## df[[vars$outcome[i]]] 7.393e-04 1.442e-04 5.129 3.16e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 595.7 on 2325 degrees of freedom
## (13297 observations deleted due to missingness)
## Multiple R-squared: 0.01119, Adjusted R-squared: 0.01076
## F-statistic: 26.3 on 1 and 2325 DF, p-value: 3.16e-07
##
## [1] "p-value: 0.000144159134177366"
## [1] "TEST RESULT: Ho rejects"
## [1] "Population group:non_displaced"
## [1] "Predicotr variable:fuel_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -15933 -843 -206 94 35431
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 9.504e+02 1.485e+01 63.98 <2e-16 ***
## df[[vars$outcome[i]]] 2.280e-03 1.581e-04 14.43 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1762 on 10582 degrees of freedom
## (5040 observations deleted due to missingness)
## Multiple R-squared: 0.01929, Adjusted R-squared: 0.0192
## F-statistic: 208.1 on 1 and 10582 DF, p-value: < 2.2e-16
##
## [1] "p-value: 0.00015806990934777"
## [1] "TEST RESULT: Ho rejects"
## [1] "Population group:non_displaced"
## [1] "Predicotr variable:debt_exp"
## [1] "Outcome variable:debt_amount"
## [1] "Summary:"
##
## Call:
## lm(formula = df[[vars$predictor[i]]] ~ df[[vars$outcome[i]]],
## weights = df$weight)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -18370 -1133 -739 -146 227652
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.627e+02 6.608e+01 8.515 < 2e-16 ***
## df[[vars$outcome[i]]] 3.962e-03 7.032e-04 5.634 1.8e-08 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7847 on 10601 degrees of freedom
## (5021 observations deleted due to missingness)
## Multiple R-squared: 0.002986, Adjusted R-squared: 0.002892
## F-statistic: 31.75 on 1 and 10601 DF, p-value: 1.803e-08
##
## [1] "p-value: 0.000703184040005687"
## [1] "TEST RESULT: Ho rejects"
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