scholarly journals Asking About Numbers: Why and How

2013 ◽  
Vol 21 (1) ◽  
pp. 48-69 ◽  
Author(s):  
Stephen Ansolabehere ◽  
Marc Meredith ◽  
Erik Snowberg
Keyword(s):  
Measurement Error ◽  
Unemployment Rate ◽  
Economic Voting ◽  
Partisan Bias ◽  
Survey Questions ◽  
Reduce Measurement Error

Survey questions about quantities offer a number of advantages over more common qualitative questions. However, concerns about survey respondents' abilities to accurately report numbers have limited the use of quantitative questions. This article shows quantitative questions are feasible and useful for the study of economic voting. First, survey respondents are capable of accurately assessing familiar economic quantities, such as the price of gas. Second, careful question design—in particular providing respondents with benchmark quantities—can reduce measurement error due to respondents not understanding the scale on which more complex quantities, such as the unemployment rate, are measured. Third, combining quantitative and qualitative questions sheds light on where partisan bias enters economic assessments: in perceiving, judging, or reporting economic quantities.

Basic concepts

2015 ◽  
Author(s):  
David L. Streiner ◽  
Geoffrey R. Norman ◽  
John Cairney
Keyword(s):  
Measurement Error ◽  
Scale Reliability ◽  
Key Concepts ◽  
Reduce Measurement Error ◽  
Diagnosis And Classification ◽  
Basic Concepts

This chapter begins by introducing the readers to finding existing scales that may meet their needs. It briefly summarizes the key concepts they should look for in a scale—reliability, validity, and feasibility. It discusses what is meant by these various terms and how they are measured. The chapter also contrasts the categorical versus the dimensional approaches to diagnosis and classification. Finally, it compares the medical versus the psychometric ways of trying to reduce measurement error.

What Doesn’t Get Measured Does Exist: Improving the Accuracy of Computer-Aided Text Analysis

2016 ◽  
Vol 44 (7) ◽  
pp. 2909-2933 ◽  
Author(s):  
Aaron F. McKenny ◽  
Herman Aguinis ◽  
Jeremy C. Short ◽  
Aaron H. Anglin
Keyword(s):  
Measurement Error ◽  
Text Analysis ◽  
Best Practice ◽  
Error Variance ◽  
Theory And Practice ◽  
Future Research ◽  
Specific Factor ◽  
Computer Aided ◽  
Measurement Error Variance ◽  
Reduce Measurement Error

Computer-aided text analysis (CATA) is a form of content analysis that enables the measurement of constructs by processing text into quantitative data based on the frequency of words. CATA has been proposed as a useful measurement approach with the potential to lead to important theoretical advancements. Ironically, while CATA has been offered to overcome some of the known deficiencies in existing measurement approaches, we have lagged behind in regard to assessing the technique’s measurement rigor. Our article addresses this knowledge gap and describes important implications for past as well as future research using CATA. First, we describe three sources of measurement error variance that are particularly relevant to studies using CATA: transient error, specific factor error, and algorithm error. Second, we describe and demonstrate how to calculate measurement error variance with the entrepreneurial orientation, market orientation, and organizational ambidexterity constructs, offering evidence that past substantive conclusions have been underestimated. Third, we offer best-practice recommendations and demonstrate how to reduce measurement error variance by refining existing CATA measures. In short, we demonstrate that although measurement error variance in CATA has not been measured thus far, it does exist and it affects substantive conclusions. Consequently, our article has implications for theory and practice, as well as how to assess and minimize measurement error in future CATA research with the goal of improving the accuracy of substantive conclusions.

Using the area under the curve to reduce measurement error in predicting young adult blood pressure from childhood measures

2004 ◽  
Vol 23 (22) ◽  
pp. 3421-3435 ◽  
Author(s):  
Nancy R. Cook ◽  
Bernard A. Rosner ◽  
Wei Chen ◽  
Sathanur R. Srinivasan ◽  
Gerald S. Berenson
Keyword(s):  
Blood Pressure ◽  
Young Adult ◽  
Measurement Error ◽  
Area Under The Curve ◽  
Reduce Measurement Error

scholarly journals Digging into the Pocketbook: Evidence on Economic Voting from Income Registry Data Matched to a Voter Survey

2017 ◽  
Vol 111 (4) ◽  
pp. 771-785 ◽  
Author(s):  
ANDREW J. HEALY ◽  
MIKAEL PERSSON ◽  
ERIK SNOWBERG
Keyword(s):  
Strong Evidence ◽  
Historical Data ◽  
Economic Voting ◽  
Vote Choice ◽  
Economic Conditions ◽  
Economic Evaluations ◽  
Economic Data ◽  
Partisan Bias ◽  
Economic Information ◽  
Financial Conditions

To paint a fuller picture of economic voters, we combine personal income records with a representative election survey. We examine three central topics in the economic voting literature: pocketbook versus sociotropic voting, the effects of partisanship on economic evaluations, and voter myopia. First, we show that voters who appear in survey data to be voting based on the national economy are, in fact, voting equally on the basis of their personal financial conditions. Second, there is strong evidence of both partisan bias and economic information in economic evaluations, but personal economic data is required to separate the two. Third, although in experiments and aggregate historical data recent economic conditions appear to drive vote choice, we find no evidence of myopia when we examine actual personal economic data.

Mass Political Attitudes and the Survey Response

1975 ◽  
Vol 69 (4) ◽  
pp. 1218-1231 ◽  
Author(s):  
Christopher H. Achen
Keyword(s):  
Public Opinion ◽  
Measurement Error ◽  
Political Attitudes ◽  
Survey Response ◽  
Opinion Survey ◽  
Public Opinion Research ◽  
Survey Questions

Students of public opinion research have argued that voters show very little consistency and structure in their political attitudes. A model of the survey response is proposed which takes account of the vagueness in opinion survey questions and in response categories. When estimates are made of this vagueness or “measurement error” and the estimates applied to the principal previous study, nearly all the inconsistency is shown to be the result of the vagueness of the questions rather than of any failure by the respondents.

scholarly journals Is there a partisan bias in the perception of the state of the economy? A comparative investigation of European countries, 2002–2016

2020 ◽  
pp. 019251212091590 ◽  
Author(s):  
Martin Okolikj ◽  
Marc Hooghe
Keyword(s):  
Economic Performance ◽  
Real Life ◽  
Economic Voting ◽  
Comparative Investigation ◽  
European Social Survey ◽  
The State ◽  
Partisan Bias ◽  
State Of The Economy ◽  
High Level ◽  
Economic Perceptions

The literature on economic voting starts from the assumptions that citizens have a sufficiently high level of knowledge about their country’s economic situation, and that they vote according to their perception of the state of the economy. However, these assumptions have been challenged as economic perceptions could be plagued by partisan bias. We use the comparative dataset of the European Social Survey to investigate partisan bias in the perception of economic performance. Firstly, we observe that the economic perceptions of both supporters and opponents of governing parties are strongly related to real-life economic indicators such as gross domestic product growth and unemployment levels. Secondly, we find that shifts in economic performance (growth and unemployment) are strongly associated with similar changes in economic perceptions among both supporters of governing parties and opposition parties. There is, however, a significant but limited partisan bias in economic perceptions in countries with high levels of unemployment.

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