This must be the report Steve Miller referred to about non-citizens registering to vote.

[rgbecker]

I questioned the 14% of illegal immigrants figure and have several problems with the report. Maybe another statistician/economist will have some comments.???

Wonder who sponsored this research which is actually just an analysis of data compiled by others.


http://www.sciencedirect.com/science/article/pii/S0261379414000973


I live in Massachusetts and there are illegal immigrants coming and going, but I'd be surprised to see any listed on the voter registration roles, much less meet up with any showing up on election day to vote.

[struggle4progress]

1. The Perils of Cherry Picking Low Frequency Events

November 5, 2014
Stephen Ansolabehere (Harvard University, PI CCES)
Samantha Luks (YouGov)
Brian F. Schaffner (University of Massachusetts, Amherst, co-­PI CCES)

The advent of large sample surveys, such as the Cooperative Congressional Election Study (CCES), has opened the possibility of measuring very low frequency events, characteristics, and behaviors in the population. This is certainly a worthy objective, but researchers must use caution when studying low probability events and behaviors, such as non-citizenship rates and voting. Even very low-level measurement error can lead to classification and prediction errors and incorrect inferences in analyses.

This paper documents how low-level measurement error for survey questions generally agreed to be highly reliable can lead to large prediction errors in large sample surveys, such as the CCES. The example for this analysis is Richman, Chattha, and Earnest (2014), which presents a biased estimate of the rate at which non-citizens voted in recent elections. The results, we show, are completely accounted for by very low frequency measurement error; further, the likely percent of non-citizen voters in recent US elections is 0 ...

... misclassifications can explain completely the observed low rate of a behavior, such as voting, among a relatively rare or low-frequency group, such as non-citizens. Suppose that 70 percent of those with a given characteristic (e.g., citizens) engage in a behavior (e.g., voting). Suppose, further, that none of the people without the characteristic (e.g., non-citizens) are allowed to engage in the behavior in question (e.g., vote in federal elections). Based on these suppositions, of the 19 misclassified people, we expect 13 (70%) to be incorrectly determined to be non-citizen voters while 0 correctly classified non-citizens would be voters. Hence, a 0.1 percent rate of misclassification—a very low level of measurement error—would lead researchers to expect to observe that 13 of 519 (2.8 percent) people classified as non-citizens voted in the election, when those results are due entirely to measurement error, and no non-citizens actually voted ...

http://projects.iq.harvard.edu/cces/news/perils-cherry-picking-low-frequency-events-large-sample-surveys

[Lucinda]

2. TY!

[struggle4progress]

3. Trumps Claims About Illegal Votes Are Nonsense

The real number of non-citizen voters is more like zero.
By BRIAN SCHAFFNER November 29, 2016

... Trump is making news with his .. claim .. he would have won the national popular vote if millions of non-citizens had not voted ... As evidence, he and his staff are pointing to a study by Jesse Richman and his co-authors that was published in .. Electoral Studies ...

... Their chief claim, and the one that made headlines, was that as many as 14 percent of noncitizens living in the United States had cast votes in recent elections. As soon as I saw that figure, I knew it was almost certainly nonsense, but what was troubling was that the “evidence” the scholars were pointing to was from a survey that I coordinate along with my colleagues Stephen Ansolabehere of Harvard University and Samantha Luks from the survey research firm YouGov. The survey is the Cooperative Congressional Election Study—a project that interviews tens of thousands of respondents every election year about their views on politics. A wealth of excellent research has come from this dataset in the past decade, providing important insights about our political world. Unfortunately, the Richman study doesn’t fall into that category. It is bad research, because it fails to understand basic facts about the data it uses.

... The authors were essentially basing their claims on two pieces of data associated with the large survey—a question that asks people whether they are citizens and official vote records to which each respondent has been matched to determine whether he or she had voted. Both these pieces of information include some small amounts of measurement error, as is true of all survey questions. What the authors failed to consider is that measurement error was entirely responsible for their results ...

... we actually took 19,000 respondents from one of the surveys that Richman used (the 2010 study) and we interviewed them again in 2012. A total of 121 of the 19,000 respondents (.64 percent) identified themselves as immigrant non-citizens when they first answered the survey in 2010. However, when asked the question again in 2012, 36 of the 121 selected a different response, indicating that they were citizens. Even more telling was this: 20 respondents identified themselves as citizens in 2010 but then in 2012 changed their answers to indicate that they were non-citizens. It is highly unrealistic to go from being a citizen in 2010 to a non-citizen in 2012, which provides even stronger evidence that some people were providing incorrect responses to this question for idiosyncratic reasons ...

http://www.politico.com/magazine/story/2016/11/donald-trump-illegal-votes-evidence-debunked-214487

[rgbecker]

4. Then there is this:

http://www.politifact.com/truth-o-meter/statements/2016/oct/24/donald-trump/donald-trump-wrongly-says-14-percent-noncitizens-a/



It looks to me like the researchers are conflating the Census's number of 19 million non citizens out of a population of 3xx million with the data base's number of 121 (or actually 85) out of 19,000. They work from those numbers and come up with nonsense.