Models 05/13

h1: close proximity

population density
public transit

h2: greater travel

tourism employment
% working outside county

h3: socioeconomic status

median income
college
% without health insurance
poverty rate

h4: race

black
hispanic
asian
other
neighborhood diversity

other controls

age
gender
orleans parish
new orleans metro (outside county)
other metro

case6 <- read.csv("~/Dropbox (ASU)/Papers/Neighborhood COVID/Data/FullData.csv")
     
## reading in shapefile
tractLA <- shapefile('~/Dropbox (ASU)/Papers/Neighborhood COVID/Data/tl_2019_22_tract/tl_2019_22_tract.shp')


tractLA2 <- merge(tractLA, case6, by.x="GEOID",  by.y="Tract.ID")

f1 <- cpcln~ popdens+pubtransit+ outsidecounty+tourismemp+log(medinc)+collegepct+noinsurance+povpct+blackpct+hisppct+asianpct+otherracepct+DiversityIndex+over70pct+male+orleansparish+nolametro+othermetro

summary(ols <-lm(f1, data=tractLA2@data))

## 
## Call:
## lm(formula = f1, data = tractLA2@data)
## 
## Residuals:
##        Min         1Q     Median         3Q        Max 
## -0.0080459 -0.0020939 -0.0002738  0.0013618  0.0272571 
## 
## Coefficients:
##                  Estimate Std. Error t value Pr(>|t|)    
## (Intercept)     7.570e-03  7.763e-03   0.975 0.329702    
## popdens        -3.997e-08  6.184e-08  -0.646 0.518209    
## pubtransit      8.342e-03  4.162e-03   2.004 0.045283 *  
## outsidecounty   3.589e-03  7.825e-04   4.587 5.05e-06 ***
## tourismemp     -5.651e-04  2.279e-03  -0.248 0.804178    
## log(medinc)    -9.384e-04  6.883e-04  -1.363 0.173023    
## collegepct     -3.550e-03  1.177e-03  -3.016 0.002625 ** 
## noinsurance    -5.007e-03  3.030e-03  -1.652 0.098778 .  
## povpct         -7.577e-03  1.931e-03  -3.925 9.24e-05 ***
## blackpct        9.547e-03  6.646e-04  14.364  < 2e-16 ***
## hisppct         9.420e-03  2.836e-03   3.322 0.000925 ***
## asianpct        7.857e-03  3.809e-03   2.063 0.039371 *  
## otherracepct    1.413e-02  5.030e-03   2.809 0.005068 ** 
## DiversityIndex -9.346e-04  8.768e-04  -1.066 0.286723    
## over70pct       1.997e-02  3.292e-03   6.066 1.83e-09 ***
## male            1.586e-03  2.715e-03   0.584 0.559295    
## orleansparish   1.037e-02  7.008e-04  14.791  < 2e-16 ***
## nolametro       7.894e-03  4.914e-04  16.066  < 2e-16 ***
## othermetro      1.031e-03  3.732e-04   2.763 0.005833 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.003719 on 1043 degrees of freedom
##   (86 observations deleted due to missingness)
## Multiple R-squared:  0.6539, Adjusted R-squared:  0.6479 
## F-statistic: 109.5 on 18 and 1043 DF,  p-value: < 2.2e-16

covid_nbq <- poly2nb(tractLA2)  #Queen’s neighborhood
covid_nbq_w <- nb2listw(covid_nbq, style="W")

## Spatial Lag Model

summary(covid_LAG <- lagsarlm(f1, data = tractLA2@data, covid_nbq_w))

## Warning: Function lagsarlm moved to the spatialreg package

## Warning in spatialreg::lagsarlm(formula = formula, data = data, listw = listw, : inversion of asymptotic covariance matrix failed for tol.solve = 1e-10 
##   reciprocal condition number = 4.91482e-13 - using numerical Hessian.

## 
## Call:spatialreg::lagsarlm(formula = formula, data = data, listw = listw, 
##     na.action = na.action, Durbin = Durbin, type = type, method = method, 
##     quiet = quiet, zero.policy = zero.policy, interval = interval, 
##     tol.solve = tol.solve, trs = trs, control = control)
## 
## Residuals:
##         Min          1Q      Median          3Q         Max 
## -0.00962959 -0.00170899 -0.00020511  0.00112188  0.02643301 
## 
## Type: lag 
## Coefficients: (numerical Hessian approximate standard errors) 
##                   Estimate  Std. Error z value  Pr(>|z|)
## (Intercept)     7.1205e-03  7.0436e-03  1.0109 0.3120599
## popdens        -5.5327e-08  6.3008e-08 -0.8781 0.3798922
## pubtransit      4.8166e-03  3.9455e-03  1.2208 0.2221610
## outsidecounty   2.5708e-03  7.2008e-04  3.5702 0.0003568
## tourismemp     -2.6474e-04  2.2832e-03 -0.1159 0.9076928
## log(medinc)    -9.7902e-04  6.2768e-04 -1.5597 0.1188201
## collegepct     -2.0087e-03  1.0907e-03 -1.8417 0.0655227
## noinsurance    -2.0989e-03  2.6141e-03 -0.8029 0.4220206
## povpct         -6.4833e-03  1.7757e-03 -3.6511 0.0002612
## blackpct        7.6125e-03  6.3640e-04 11.9618 < 2.2e-16
## hisppct         7.6800e-03  2.5955e-03  2.9589 0.0030874
## asianpct        4.6196e-03  3.6710e-03  1.2584 0.2082439
## otherracepct    1.2005e-02  4.6545e-03  2.5793 0.0098991
## DiversityIndex -1.2043e-03  7.8775e-04 -1.5288 0.1263152
## over70pct       1.8622e-02  3.0726e-03  6.0605 1.357e-09
## male            2.5137e-03  2.4762e-03  1.0151 0.3100396
## orleansparish   6.5191e-03  7.2079e-04  9.0443 < 2.2e-16
## nolametro       4.9693e-03  5.1688e-04  9.6140 < 2.2e-16
## othermetro      7.7331e-04  3.4454e-04  2.2445 0.0248030
## 
## Rho: 0.38426, LR test value: 111.83, p-value: < 2.22e-16
## Approximate (numerical Hessian) standard error: 0.034216
##     z-value: 11.23, p-value: < 2.22e-16
## Wald statistic: 126.12, p-value: < 2.22e-16
## 
## Log likelihood: 4499.776 for lag model
## ML residual variance (sigma squared): 1.1874e-05, (sigma: 0.0034458)
## Number of observations: 1062 
## Number of parameters estimated: 21 
## AIC: -8957.6, (AIC for lm: -8847.7)

## Spatial Error Model


summary(covid_error <- errorsarlm(f1, data = tractLA2@data, covid_nbq_w))

## Warning: Function errorsarlm moved to the spatialreg package

## Warning in spatialreg::errorsarlm(formula = formula, data = data, listw = listw, : inversion of asymptotic covariance matrix failed for tol.solve = 1e-10 
##   reciprocal condition number = 1.0626e-12 - using numerical Hessian.

## 
## Call:
## spatialreg::errorsarlm(formula = formula, data = data, listw = listw, 
##     na.action = na.action, Durbin = Durbin, etype = etype, method = method, 
##     quiet = quiet, zero.policy = zero.policy, interval = interval, 
##     tol.solve = tol.solve, trs = trs, control = control)
## 
## Residuals:
##        Min         1Q     Median         3Q        Max 
## -0.0093480 -0.0017502 -0.0002467  0.0010736  0.0256510 
## 
## Type: error 
## Coefficients: (asymptotic standard errors) 
##                   Estimate  Std. Error z value  Pr(>|z|)
## (Intercept)     5.1918e-03  7.3363e-03  0.7077 0.4791405
## popdens        -7.9267e-08  6.4276e-08 -1.2332 0.2174881
## pubtransit      4.1676e-03  4.0749e-03  1.0228 0.3064249
## outsidecounty   1.9973e-03  8.8236e-04  2.2635 0.0236022
## tourismemp     -4.3363e-04  2.1660e-03 -0.2002 0.8413265
## log(medinc)    -7.6150e-04  6.5456e-04 -1.1634 0.2446738
## collegepct     -3.5503e-03  1.2895e-03 -2.7532 0.0059020
## noinsurance    -1.4303e-03  2.8530e-03 -0.5013 0.6161254
## povpct         -6.4142e-03  1.7958e-03 -3.5717 0.0003547
## blackpct        9.0435e-03  7.3192e-04 12.3558 < 2.2e-16
## hisppct         7.4470e-03  2.8598e-03  2.6040 0.0092131
## asianpct        5.0881e-03  4.1951e-03  1.2129 0.2251776
## otherracepct    1.1295e-02  5.0665e-03  2.2293 0.0257917
## DiversityIndex -1.9783e-03  8.8714e-04 -2.2299 0.0257529
## over70pct       2.0194e-02  3.1723e-03  6.3656 1.945e-10
## male            3.9217e-03  2.4534e-03  1.5985 0.1099383
## orleansparish   1.0960e-02  8.8853e-04 12.3352 < 2.2e-16
## nolametro       8.0732e-03  6.6716e-04 12.1008 < 2.2e-16
## othermetro      1.0125e-03  5.0716e-04  1.9963 0.0458977
## 
## Lambda: 0.44639, LR test value: 113.45, p-value: < 2.22e-16
## Approximate (numerical Hessian) standard error: 0.037947
##     z-value: 11.764, p-value: < 2.22e-16
## Wald statistic: 138.38, p-value: < 2.22e-16
## 
## Log likelihood: 4500.588 for error model
## ML residual variance (sigma squared): 1.1722e-05, (sigma: 0.0034238)
## Number of observations: 1062 
## Number of parameters estimated: 21 
## AIC: -8959.2, (AIC for lm: -8847.7)

Models 05/13

van Holm

5/13/2020