# Correction for Measurement Errors in Survey Research: Necessary and Possible

@article{Saris2016CorrectionFM, title={Correction for Measurement Errors in Survey Research: Necessary and Possible}, author={Willem E. Saris and M{\'e}lanie Revilla}, journal={Social Indicators Research}, year={2016}, volume={127}, pages={1005-1020} }

Survey research is the most frequently used data collection method in many disciplines. Nearly, everybody agrees that such data contain serious measurement errors. However, only few researchers try to correct for them. If the measurement errors in the variables vary, the comparison of the sizes of effects of these variables on each other will be wrong. If the sizes of the measurement errors are different across countries, cross-national comparisons of relationships between variables cannot be… Expand

#### 36 Citations

Correcting Correlation and Covariance Matrices for Measurement Errors Before Further Analysis

- Computer Science
- 2021

It is shown that this approach to correct for measurement errors in research can be generalized to studies that use a mixture of simple and complex concepts measured by several questions, and the parameters of the models are automatically corrected for measurement mistakes. Expand

Does correction for measurement error have an effect on the structure and comparability of basic human values

- Computer Science
- 2015

This study shows that the correction for measurement error provides additional support for the validity of a new value structure and it also sheds some new light on cross-cultural equivalence. Expand

Detecting faking responses during empirical research: a study in a developing country environment

- Psychology
- 2021

Purpose
Several research studies on Lean Six Sigma (LSS) have been done using the survey methodology. However, the use of surveys often relies on the measurement of variables, which cannot be… Expand

The Quality of Survey Questions in Spain: A Cross-National Comparison

- 2021

Most social research collects data about abstract concepts (e.g., attitudes) using survey questions. However, survey data suffer from measurement errors that affect substantive conclusions. When… Expand

Correction for measurement error in invariance testing: An illustration using SQP

- Computer Science, Medicine
- PloS one
- 2020

It is shown that correction for measurement error offers a viable way to ensure that non-invariant parameters are actually caused by differences in the data and not caused by the measurement method. Expand

Two Approaches to Evaluate Measurement Quality in Online Surveys: An Application Using the Norwegian Citizen Panel

- Computer Science
- 2017

Evaluating the measurement quality of a set of survey questions from two Multitrait-Multimethod experiments implemented in the 5th wave of the Norwegian Citizen Panel concludes that SQP can provide as accurate quality predictions as MTMM can estimate the quality for web survey questions. Expand

Quality of Different Scales in an Online Survey in Mexico and Colombia

- Geography
- 2015

The formulation of theories and hypotheses is done at the level of concepts. These concepts are often tested by operationalizing them using survey questions. However, measurement errors make it… Expand

The impact of mode of data collection on measures of subjective wellbeing

- Sociology
- 2018

Measures on quality of life are now widely available and questions such as life satisfaction and happiness are common in social surveys, providing invaluable information to researchers and policy… Expand

Memory Effects in Repeated Survey Questions: Reviving the Empirical Investigation of the Independent Measurements Assumption

- Psychology
- 2020

It is common to repeat survey questions in the social sciences, for example to estimate test-retest reliability or in pretest-posttest experimental designs. An underlying assumption is that the… Expand

A classification of response scale characteristics that affect data quality: a literature review

- Computer Science, Medicine
- Quality & quantity
- 2018

This paper provides an updated and detailed classification of the design decisions that matter in questionnaire development, and a summary of what is said in the literature about their impact on data quality. Expand

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