What is he best known for?
The fields of study he is best known for:
- Statistics
- Social science
- Law
The scientist’s investigation covers issues in Statistics, Structural equation modeling, Econometrics, Survey research and Design evaluation.
As part of his studies on Statistics, Willem E. Saris frequently links adjacent subjects like Social psychology.
The study incorporates disciplines such as Overtime and Learning effect in addition to Social psychology.
Covariance and Estimation of covariance matrices is closely connected to Applied mathematics in his research, which is encompassed under the umbrella topic of Structural equation modeling.
His work on Non-response bias as part of general Econometrics research is frequently linked to Mixed mode, bridging the gap between disciplines.
His Data collection study combines topics in areas such as Data quality and Operations research.
His most cited work include:
- Structural equation modelling (616 citations)
- Design, Evaluation, and Analysis of Questionnaires for Survey Research (389 citations)
- Power of the likelihood ratio test in covariance structure analysis (371 citations)
What are the main themes of his work throughout his whole career to date?
Willem E. Saris mainly focuses on Statistics, Econometrics, Quality, Social psychology and Observational error.
Many of his research projects under Statistics are closely connected to Estimation with Estimation, tying the diverse disciplines of science together.
Willem E. Saris has included themes like Structural equation modeling and Test in his Econometrics study.
The Structural equation modeling study which covers Applied mathematics that intersects with Mathematical optimization.
When carried out as part of a general Quality research project, his work on Data quality is frequently linked to work in Ballot, therefore connecting diverse disciplines of study.
His studies in Personality and Affect are all subfields of Social psychology research.
He most often published in these fields:
- Statistics (21.08%)
- Econometrics (17.30%)
- Quality (16.22%)
What were the highlights of his more recent work (between 2011-2021)?
- Quality (16.22%)
- Statistics (21.08%)
- European Social Survey (8.11%)
In recent papers he was focusing on the following fields of study:
Willem E. Saris mainly investigates Quality, Statistics, European Social Survey, Econometrics and Observational error.
His Quality study integrates concerns from other disciplines, such as Mathematical optimization, Applied psychology and World Wide Web.
His biological study focuses on Response bias.
His biological study spans a wide range of topics, including Reliability, Data quality and Marketing.
His Sample size determination study frequently draws parallels with other fields, such as Structural equation modeling.
His research investigates the link between Structural equation modeling and topics such as Performance management that cross with problems in Sample.
Between 2011 and 2021, his most popular works were:
- Choosing the Number of Categories in Agree–Disagree Scales (156 citations)
- Design, Evaluation, and Analysis of Questionnaires for Survey Research: Saris/Design, Evaluation, and Analysis of Questionnaires for Survey Research (83 citations)
- The internationalization of small firms: The relationship between the global mindset and firms’ internationalization behavior (51 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Social science
- Law
His scientific interests lie mostly in Statistics, Quality, European Social Survey, Social psychology and Econometrics.
Statistics is closely attributed to Acquiescence in his work.
His studies in Quality integrate themes in fields like Structural equation modeling, Monte Carlo method, World Wide Web and Face-to-face.
He has researched European Social Survey in several fields, including Confirmatory factor analysis, Orientation and Affect.
His studies deal with areas such as Sample, Middle management and Power as well as Social psychology.
His Econometrics research integrates issues from Predictive power, Data quality and Homogeneity.
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