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7 results for “from:Maaz Gardezi”

Neighborhood matrix from poly2nb (spdep package)
Maaz Gardezi · Nov 7, 2016 · r-sig-geo

Thanks, Ill look into alternative ways of finding the neighborhood matrix. Both the vignette's were helpful. Maaz [[alternative HTML version deleted]]

Aggregating census tract to county
Maaz Gardezi · Dec 23, 2016 · r-sig-geo

Hello, Can anyone tell me what's the most appropriate method to aggregate census tract data to the county level? Best Maaz [[alternative HTML version deleted]]

getting standard errors of prediction (SAR/CAR) in spdep
Maaz Gardezi · Oct 26, 2016 · r-sig-geo

Hello, Does anyone know if there's a way that the package 'spdep' can give standard errors of the prediction (for either SAR or CAR model)? I'm using the spautolm function. Regards, Maaz PhD Candidate and Graduate Research Assistant...

Neighborhood matrix from poly2nb (spdep package)
Maaz Gardezi · Nov 4, 2016 · r-sig-geo

Hi, I'm trying to extract the 'neighborhood matrix' from the poly2nb function. I can see the neighbors for each polygon, e.g. 1 has neighbors 2, 3, 5, 6. I try to convert this matrix into a data frame...

statistical significance of group level intercepts in glmer
Maaz Gardezi · May 29, 2017 · r-sig-mixed-models

Hello, I am using glmer to model a mixed effects logistic regression. The output below shows the random intercepts and slope (zcwcexp) for 22 groups. I was wondering if there is any way of finding whether these are statistically significant...

Aggregating census tract to county
Maaz Gardezi · Dec 23, 2016 · r-sig-geo

Juta, Thanks for your reply. My question also has a methodological dimension to it. Would it be OK to aggregate census tract data (on lets say female headed household) to the county level by simply adding all the tracts together...

statistical significance of group level intercepts in glmer
Maaz Gardezi · May 30, 2017 · r-sig-mixed-models

Thanks for the clarification. Maaz On May 30, 2017 9:00 AM, "Ben Bolker" <bbolker at gmail.com> wrote: > Unfortunately, you *can't* test significance of conditional modes (the > values that ranef()) returns; this is the price you pay for...

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