slideWakeMatch {mwa}

Auxiliary Function to Match Data and Estimate Treatment Effects

Description

Method takes the output of slidingWake, matches observations using cem and estimates treatment effects using linear models (lm or att) or a count dependent variable model (glm.nb).

Usage

slideWakeMatch(wakes, alpha1, matchColumns, estimation, formula, weighted,
               estimationControls, TCM, match.default, ...)

Arguments

wakes

data.frame. See “wakes” in the description of matchedwake for details.

alpha1

significance level used for the analysis and plots. Default = 0.05.

matchColumns

vector of Strings indicating the columns to match on.

estimation

String specifying method used for estimation.

formula

String specifying the model used for estimation.

weighted

Boolean specifying whether regression is weighted.

estimationControls

vector of Strings indicating additional control dimensions to be included in the estimation.

TCM

Boolean to select whether the method should match on counts of previous treatment and control instances.

match.default

Boolean to select whether observations are matched using cem.

...

optional parameters that can be passed to the methods used for matching and estimation.

Details

See the description of matchedwake for details.

Value

Returns a list with the following slots:

estimates

data.frame with estimates and p values for all spatial and temporal windows considered.

matching

data.frame with detailed matching statistics for all spatial and temporal windows considered.

SUTVA

data.frame with detailed statistics on the degree of overlaps of the spatiotemporal cylinders.

wakes

data.frame.

See the description of matchedwake for details.

Author(s)

Sebastian Schutte and Karsten Donnay.

References

Schutte, S., Donnay, K. (2014). “Matched wake analysis: Finding causal relationships in spatiotemporal event data.” Political Geography 41:1-10.

See Also

matchedwake, slidingWake