Posts by Tags

ACS

Creating Survey Weights in R Using Census Data

18 minute read

Published:

In survey research, the composition of a sample may differ notably from the population being modeled across important characteristics (e.g. race, age, education, party identification). These sampling errors often reflect systematic bias which can pose a threat to accuracy and the researcher’s ability to make inferences using the data, especially if the error is correlated with the variables of interest.

Black Americans

CES

Educational Polarization in the CES

8 minute read

Published:

Recently, CES Researcher Pia Deshpande wrote an excellent tutorial detailing how to plot trends over time using CES data — I highly encourage anyone who hasn’t yet read the piece to promptly do so! This style of plot pairs particularly well with the cumulative CES Common Content dataset created by Shiro Kuriwaki. Together, these resources can help us to understand an issue that has received increased attention in recent months: educational polarization.

Using the CES to Examine Young Voters

5 minute read

Published:

July 1 marked 50 years since the ratification of the 26th Amendment to the United States Constitution, which legally extended the right to vote to those over the age of 18. Young voters have played a vital – at times, even decisive – role in elections since. But decades after the franchise was extended to 18-, 19-, and 20- year-olds, how does their voting rates compare to American adults overall?

CIRCLE

Using the CES to Examine Young Voters

5 minute read

Published:

July 1 marked 50 years since the ratification of the 26th Amendment to the United States Constitution, which legally extended the right to vote to those over the age of 18. Young voters have played a vital – at times, even decisive – role in elections since. But decades after the franchise was extended to 18-, 19-, and 20- year-olds, how does their voting rates compare to American adults overall?

Census

Creating Survey Weights in R Using Census Data

18 minute read

Published:

In survey research, the composition of a sample may differ notably from the population being modeled across important characteristics (e.g. race, age, education, party identification). These sampling errors often reflect systematic bias which can pose a threat to accuracy and the researcher’s ability to make inferences using the data, especially if the error is correlated with the variables of interest.

Data For Progress

Lucid

college education

Educational Polarization in the CES

8 minute read

Published:

Recently, CES Researcher Pia Deshpande wrote an excellent tutorial detailing how to plot trends over time using CES data — I highly encourage anyone who hasn’t yet read the piece to promptly do so! This style of plot pairs particularly well with the cumulative CES Common Content dataset created by Shiro Kuriwaki. Together, these resources can help us to understand an issue that has received increased attention in recent months: educational polarization.

educational polarization

Educational Polarization in the CES

8 minute read

Published:

Recently, CES Researcher Pia Deshpande wrote an excellent tutorial detailing how to plot trends over time using CES data — I highly encourage anyone who hasn’t yet read the piece to promptly do so! This style of plot pairs particularly well with the cumulative CES Common Content dataset created by Shiro Kuriwaki. Together, these resources can help us to understand an issue that has received increased attention in recent months: educational polarization.

race and ethnicity

survey

Creating Survey Weights in R Using Census Data

18 minute read

Published:

In survey research, the composition of a sample may differ notably from the population being modeled across important characteristics (e.g. race, age, education, party identification). These sampling errors often reflect systematic bias which can pose a threat to accuracy and the researcher’s ability to make inferences using the data, especially if the error is correlated with the variables of interest.

An Introduction to Using the {survey} Package in R

7 minute read

Published:

Survey research commonly relies on weights to reduce bias and produce a representative sample for a given population of interest. Weighted survey data produces a value assigned to each observation in the data that increases or decreases that observation’s influence (or weight) when performing statistical operations using the data.

survey data

Creating Survey Weights in R Using Census Data

18 minute read

Published:

In survey research, the composition of a sample may differ notably from the population being modeled across important characteristics (e.g. race, age, education, party identification). These sampling errors often reflect systematic bias which can pose a threat to accuracy and the researcher’s ability to make inferences using the data, especially if the error is correlated with the variables of interest.

An Introduction to Using the {survey} Package in R

7 minute read

Published:

Survey research commonly relies on weights to reduce bias and produce a representative sample for a given population of interest. Weighted survey data produces a value assigned to each observation in the data that increases or decreases that observation’s influence (or weight) when performing statistical operations using the data.

survey methodology

tidyverse

Creating Survey Weights in R Using Census Data

18 minute read

Published:

In survey research, the composition of a sample may differ notably from the population being modeled across important characteristics (e.g. race, age, education, party identification). These sampling errors often reflect systematic bias which can pose a threat to accuracy and the researcher’s ability to make inferences using the data, especially if the error is correlated with the variables of interest.

An Introduction to Using the {survey} Package in R

7 minute read

Published:

Survey research commonly relies on weights to reduce bias and produce a representative sample for a given population of interest. Weighted survey data produces a value assigned to each observation in the data that increases or decreases that observation’s influence (or weight) when performing statistical operations using the data.

turnout

youth voting

Using the CES to Examine Young Voters

5 minute read

Published:

July 1 marked 50 years since the ratification of the 26th Amendment to the United States Constitution, which legally extended the right to vote to those over the age of 18. Young voters have played a vital – at times, even decisive – role in elections since. But decades after the franchise was extended to 18-, 19-, and 20- year-olds, how does their voting rates compare to American adults overall?