Introduction to R 'plm' package (3)

In the ‘plm’ package blog (2),  we’ve gotten regression outputs for both fixed and random effect models. One common question after getting regression output is to figure out which model should be chosen using Hausman test. The fixed effect output is names as “grun.fe” and the random effect output is names as “grun.re”. The function […]

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Introduction to R ‘plm’ package (1)

This blog is an introduction to use ‘plm’ package for panel data analysis. Panel data means datasets with the same observations (respondents) and variables across different time units (such as year, month). And it’s common for researchers to have an unbalanced panel dataset in practice (for example, GDP data could be missing in different years […]

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Introduction to R 'survey' package (3)

After defining your survey dataset (please refer back to ‘survey’ package blog (1) & (2) ), you could use the functions below to describe your survey data and estimate population. Let’s still use apiclus1 data. After svydesign() function, you have a designed survey dataset, dclus1, which we designed in the last week. In this dataset, […]

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Introduction to R package ‘survey’ (2)

Here are more types of survey data except the case (simple random sample) we introduced before. The ‘survey’ package contains several sample datasets from the California Academic Performance Index. After installing and loading the ‘survey’ package, you could import these data samples using command: data(api). And you will see 5 datasets are loaded in R, […]

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Using R with ArcGIS

With a successful collaboration between DSSC and ESRI, a hands-on workshop on ESRI R plugin was presented by Shaun Walbridge, a senior developer from ESRI, on Wednesday, April 20. Shaun provided an in-depth tutorial on how to use R in ESRI, and answered questions from students and librarians. Our audiences were from a broad background: […]

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