spacom (version 0.9-3)

SpawMLResidMoran: Testing the (residual) spatial dependency

Description

Test of spatial dependency in contextual level residuals from (spatially weighted) multilevel models. The spatial dependency is operationalized by Moran's I coefficient for spatial auto-correlation.

Usage

SpawMLResidMoran(srawe.obj, distance.matrix, bandwidths,
  kernel = NULL, confidence.intervals = c(0.95))

Arguments

srawe.obj

ResampledSpawMLOutput, or a vector of residuals from a SpawMLOutput or matrix of residuals from a ResampleExactSpawMLOutput

distance.matrix

square matrix of dimension $n\times n$, where $n$ is the number of contextual units.

bandwidths

vector of bandwidths for which to compute Moran's I.

kernel

function applied to the distance matrix. By default NULL, in which case the kernel function $$w_{ij}=f(d,h) = \left(\frac{1}{2}\right)^{d_{ij}^2/h^2}$$ is used, where $w_{ij}, d_{ij}, h$ are elements of the weight matrix $\mathbf{W}

confidence.intervals

vector of conficence intervals. Defaults to c(.95) which corresponds to 95 %.

Value

Examples

# Residual spatial autocorrelation

## for residuals from ResampleAggregateSpawML
# load individual level data, remove collective guilt assignment for the
# data frame, and remove NA's 
data(traces_ind) 

traces_ind <- traces_ind[,-7]
traces_ind <- na.exclude(traces_ind)

# load contextual indicator for aggregation
data(traces_event) 

# load precise contextual indicator
data(homog_census) 

# load distance matrix and create weights
data(d_geo) 
geow_100 <- WeightMatrix(d_geo, bandwidth=100)

# perform ResampleAggregateSpawML
acc_w_homog_100 <-
ResampleAggregateSpawML(individual.level.data=traces_ind,
  contextual.names=c("w_all", "Homog_00"), context.id="area",
  formula=cg_acc ~ victim_d + comb_d + male + age_1990 + high_school +
  higher_edu + (1|area), contextual.data=traces_event,
  precise.data=homog_census, contextual.weight.matrices=list(geow_100,
  geow_100), individual.weight.names="weight",
  aggregation.functions="weighted.mean", nb.resamples=10)


# perform SpawMLResidMoran for bandwidths 25, 50, 100, 200 

MI_acc <- SpawMLResidMoran(srawe.obj=acc_w_homog_100,
  distance.matrix=d_geo, bandwidths=c(25,50,100,200))