library(readxl)
clean_stratified <- read.csv("~/Desktop/Columbia research/Social Capital and EQI/clean_stratified.csv")
landfilllmopdata <- read_excel("/Users/zhongming/Downloads/landfilllmopdata.xlsx", sheet = "LMOP Database")
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/
library(dplyr)
df=d%>%group_by(state,county_name)%>%summarise(rate=mean(rate),landfill=n(),waste=sum(waste),gas=sum(gas))
library(stringr)
clean_stratified$county_name=str_replace(clean_stratified$county_name," County","")
ds=clean_stratified%>%left_join(df,by=c("state","county_name"))
Column `state` joining factor and character vector, coercing into character vector
ds=ds%>%mutate(waste_per=waste/total_pop,rate_per=rate/total_pop,gas_per=gas/total_pop,landfill_per=landfill/total_pop)
Gas ~ Landfill
library(lme4)
data=ds
data[c(6:52)]=scale(data[c(6:52)])
summary(lmer(gas_per ~ landfill_per+ (1|state), data=data,REML=F))
Linear mixed model fit by maximum likelihood ['lmerMod']
Formula: gas_per ~ landfill_per + (1 | state)
Data: data
AIC BIC logLik deviance df.resid
1035.1 1051.9 -513.6 1027.1 480
Scaled residuals:
Min 1Q Median 3Q Max
-6.6629 -0.2222 0.0653 0.2415 10.7035
Random effects:
Groups Name Variance Std.Dev.
state (Intercept) 0.07303 0.2702
Residual 0.45037 0.6711
Number of obs: 484, groups: state, 45
Fixed effects:
Estimate Std. Error t value
(Intercept) 0.44237 0.05806 7.619
landfill_per 1.68317 0.07464 22.551
Correlation of Fixed Effects:
(Intr)
landfill_pr 0.312
Waste ~ Landfill
summary(lmer(waste_per ~ landfill_per+ (1|state), data=data,REML=F))
Linear mixed model fit by maximum likelihood ['lmerMod']
Formula: waste_per ~ landfill_per + (1 | state)
Data: data
AIC BIC logLik deviance df.resid
3043.1 3063.2 -1517.6 3035.1 1106
Scaled residuals:
Min 1Q Median 3Q Max
-5.9276 -0.0913 -0.0102 0.0655 28.4580
Random effects:
Groups Name Variance Std.Dev.
state (Intercept) 0.1170 0.3421
Residual 0.8549 0.9246
Number of obs: 1110, groups: state, 49
Fixed effects:
Estimate Std. Error t value
(Intercept) 0.11167 0.06188 1.805
landfill_per 0.46014 0.04339 10.606
Correlation of Fixed Effects:
(Intr)
landfill_pr 0.107
Gas~ Landfil+SK
summary(lmer(gas_per ~ landfill_per+sk09+ (1|state), data=data,REML=F))
Linear mixed model fit by maximum likelihood ['lmerMod']
Formula: gas_per ~ landfill_per + sk09 + (1 | state)
Data: data
AIC BIC logLik deviance df.resid
1023.8 1044.7 -506.9 1013.8 478
Scaled residuals:
Min 1Q Median 3Q Max
-6.5190 -0.2150 0.0375 0.2565 10.6248
Random effects:
Groups Name Variance Std.Dev.
state (Intercept) 0.07275 0.2697
Residual 0.43964 0.6631
Number of obs: 483, groups: state, 44
Fixed effects:
Estimate Std. Error t value
(Intercept) 0.41860 0.05823 7.189
landfill_per 1.77545 0.07830 22.675
sk09 -0.21199 0.06041 -3.509
Correlation of Fixed Effects:
(Intr) lndfl_
landfill_pr 0.249
sk09 0.118 -0.334
Waste ~ Landfill+SK09
summary(lmer(waste_per ~ landfill_per+sk09+ (1|state), data=data,REML=F))
Linear mixed model fit by maximum likelihood ['lmerMod']
Formula: waste_per ~ landfill_per + sk09 + (1 | state)
Data: data
AIC BIC logLik deviance df.resid
3037.3 3062.3 -1513.6 3027.3 1101
Scaled residuals:
Min 1Q Median 3Q Max
-5.8033 -0.0979 -0.0096 0.0716 28.3869
Random effects:
Groups Name Variance Std.Dev.
state (Intercept) 0.1189 0.3448
Residual 0.8572 0.9259
Number of obs: 1106, groups: state, 47
Fixed effects:
Estimate Std. Error t value
(Intercept) 0.12022 0.06338 1.897
landfill_per 0.45168 0.04478 10.086
sk09 0.04176 0.05276 0.792
Correlation of Fixed Effects:
(Intr) lndfl_
landfill_pr 0.063
sk09 0.150 -0.241
airEQI~ Landfill
summary(lmer(air_EQI_22July2013 ~ landfill_per+ (1|state), data=data,REML=F))
Linear mixed model fit by maximum likelihood ['lmerMod']
Formula: air_EQI_22July2013 ~ landfill_per + (1 | state)
Data: data
AIC BIC logLik deviance df.resid
2406.0 2427.1 -1199.0 2398.0 1432
Scaled residuals:
Min 1Q Median 3Q Max
-3.6200 -0.6612 -0.0179 0.6137 7.2308
Random effects:
Groups Name Variance Std.Dev.
state (Intercept) 0.1862 0.4316
Residual 0.2833 0.5323
Number of obs: 1436, groups: state, 50
Fixed effects:
Estimate Std. Error t value
(Intercept) 0.34017 0.06458 5.268
landfill_per -0.46990 0.01652 -28.453
Correlation of Fixed Effects:
(Intr)
landfill_pr 0.003
airEQI ~ Landfill+SK
summary(lmer(air_EQI_22July2013 ~ landfill_per+sk09+ (1|state), data=data,REML=F))
Linear mixed model fit by maximum likelihood ['lmerMod']
Formula: air_EQI_22July2013 ~ landfill_per + sk09 + (1 | state)
Data: data
AIC BIC logLik deviance df.resid
2361.4 2387.8 -1175.7 2351.4 1426
Scaled residuals:
Min 1Q Median 3Q Max
-3.5804 -0.6723 -0.0252 0.6312 6.3967
Random effects:
Groups Name Variance Std.Dev.
state (Intercept) 0.1750 0.4184
Residual 0.2764 0.5257
Number of obs: 1431, groups: state, 48
Fixed effects:
Estimate Std. Error t value
(Intercept) 0.34906 0.06357 5.491
landfill_per -0.42714 0.01807 -23.636
sk09 -0.14611 0.02606 -5.608
Correlation of Fixed Effects:
(Intr) lndfl_
landfill_pr -0.019
sk09 0.046 -0.431
Waste Accept ~ landfill+SK
summary(lmer(rate_per ~ landfill_per+sk09+ (1|state), data=data,REML=F))
Linear mixed model fit by maximum likelihood ['lmerMod']
Formula: rate_per ~ landfill_per + sk09 + (1 | state)
Data: data
AIC BIC logLik deviance df.resid
3208.2 3233.4 -1599.1 3198.2 1138
Scaled residuals:
Min 1Q Median 3Q Max
-2.4679 -0.0800 -0.0261 0.0234 30.7699
Random effects:
Groups Name Variance Std.Dev.
state (Intercept) 0.08579 0.2929
Residual 0.92082 0.9596
Number of obs: 1143, groups: state, 47
Fixed effects:
Estimate Std. Error t value
(Intercept) 0.03380 0.05634 0.600
landfill_per 0.19623 0.03357 5.846
sk09 0.01316 0.04946 0.266
Correlation of Fixed Effects:
(Intr) lndfl_
landfill_pr -0.051
sk09 0.159 -0.377
Waste Accept ~ landfill
summary(lmer(rate_per ~ landfill_per+ (1|state), data=data,REML=F))
Linear mixed model fit by maximum likelihood ['lmerMod']
Formula: rate_per ~ landfill_per + (1 | state)
Data: data
AIC BIC logLik deviance df.resid
3211.8 3232.0 -1601.9 3203.8 1142
Scaled residuals:
Min 1Q Median 3Q Max
-2.5153 -0.0768 -0.0262 0.0218 30.8197
Random effects:
Groups Name Variance Std.Dev.
state (Intercept) 0.08419 0.2901
Residual 0.91885 0.9586
Number of obs: 1146, groups: state, 49
Fixed effects:
Estimate Std. Error t value
(Intercept) 0.03087 0.05501 0.561
landfill_per 0.19950 0.03104 6.428
Correlation of Fixed Effects:
(Intr)
landfill_pr 0.012
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