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MAPTILE: Stata module to map a variable
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TL;DR: maptile as mentioned in this paper generates choropleth maps, where each area is shaded according to the value of the variable being plotted, and colors the bins in increasing intensity.
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Abstract: maptile makes it easy to map a variable in Stata. It generates choropleth maps, where each area is shaded according to the value of the variable being plotted. By default, maptile divides the geographic units into equal-sized bins (corresponding to quantiles of the plotted variable), then colors the bins in increasing intensity. To generate any particular map, maptile uses a geography, which is a template for that map. These need to be downloaded and installed. If no geography currently exists for the region you want to map, you can create a new one.
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TL;DR: This study aims to analyze and discuss the relevance of functional foods and their nutritional components in individual health and their relationship with Alzheimer's disease.
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Understanding the linkages between racial/ethnic discipline gaps and racial/ethnic achievement gaps in the United States
TL;DR: This article found a modest, statistically significant, positive association between discipline gaps and achievement gaps, even after extensive covariate adjustment, in nearly all school districts in the United States with data collected by the Office of Civil Rights between 2013 and 2014.
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kmr: A Command to Correct Survey Weights for Unit Nonresponse Using Group’s Response Rates
Ercio Munoz,Salvatore Morelli +1 more
TL;DR: In this article, a Stata command, kmr, is used to estimate a micro compliance function using group's nonresponse rates, which can be used to correct survey weights for unit nonresponse.
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Enabling and constraining successful reablement: Individual and neighbourhood factors.
TL;DR: Using multilevel logistic regression to analyse management data of reablement episodes collected by Essex County Council, a UK local authority, constraining and enabling factors for successful reablements are identified.
The Impact of Increasing Community-Directed State Mental Health Agency Expenditures on Violent Crime.
TL;DR: In this paper, the authors used state mental health agency data to construct a panel of U.S. states over nine years and apply an instrumental variables empirical model with state and time fixed effects to adjust for policy endogeneity, omitted variable bias, and time trends.
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