R Dataset / Package DAAG / nsw74psidA

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How To Compute the Mean

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How To Create a Plot

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How to Compute the Median

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<iframe src="https://embed.picostat.com/r-dataset-package-daag-nsw74psida.html" frameBorder="0" width="100%" height="307px" />
Attachment Size
dataset-27177.csv 7.71 KB
Dataset License
GNU General Public License v2.0
Documentation License
GNU General Public License v2.0
Dataset Help

On this Picostat.com statistics page, you will find information about the nsw74psidA data set which pertains to A Subset of the nsw74psid1 Data Set. The nsw74psidA data set is found in the DAAG R package. You can load the nsw74psidA data set in R by issuing the following command at the console data("nsw74psidA"). This will load the data into a variable called nsw74psidA. If R says the nsw74psidA data set is not found, you can try installing the package by issuing this command install.packages("DAAG") and then attempt to reload the data. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the nsw74psidA R data set. The size of this file is about 7,897 bytes.

Documentation

A Subset of the nsw74psid1 Data Set

Description

The nsw74psidA data frame has 252 rows and 10 columns. See nsw74psid1 for more information.

Usage

nsw74psidA

Format

This data frame contains the following columns:

trt

a numeric vector

age

a numeric vector

educ

a numeric vector

black

a numeric vector

hisp

a numeric vector

marr

a numeric vector

nodeg

a numeric vector

re74

a numeric vector

re75

a numeric vector

re78

a numeric vector

Details

This data set was obtained using:

here <- age <= 40 & re74<=5000 & re75 <= 5000 & re78 < 30000

nsw74psidA <- nsw74psid1[here, ]

Examples

table(nsw74psidA$trt)
A1.lm <- lm(re78 ~ trt + (age + educ + re74 + re75) + (black +
      hisp + marr + nodeg), data = nsw74psidA)
summary(A1.lm)$coef
discA.glm <- glm(formula = trt ~ age + educ + black + hisp +
  marr + nodeg + re74 + re75, family = binomial, data = nsw74psidA)
A.scores <- predict(discA.glm)
options(digits=4)
overlap <- A.scores > -3.5 & A.scores < 3.8
A.lm <- lm(re78 ~ trt + A.scores, data=nsw74psidA, subset = overlap)
summary(A.lm)$coef
--

Dataset imported from https://www.r-project.org.

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