Post-Stratification Weighting in Organizational Surveys: A Cross-Disciplinary Tutorial

2018 ◽  
Vol 57 (2) ◽  
pp. 419-436 ◽  
Author(s):  
John T. Kulas ◽  
David H. Robinson ◽  
Jeffrey A. Smith ◽  
Donald Z. Kellar
Keyword(s):  
Organizational Surveys ◽  
Post Stratification

Impression management, candor, and microcomputer-based organizational surveys: An individual differences approach

1991 ◽  
Vol 7 (1-2) ◽  
pp. 23-32 ◽  
Author(s):  
Paul Rosenfeld ◽  
Robert A. Giacalone ◽  
Stephen B. Knouse ◽  
Linda M. Doherty ◽  
S. Mitchell Vicino ◽  
...  
Keyword(s):  
Individual Differences ◽  
Impression Management ◽  
Organizational Surveys

Realized and potential efficiency for post-stratified estimation in a national forest inventory

2021 ◽  
Author(s):  
James A. Westfall ◽  
Andrew J. Lister ◽  
John W. Coulston ◽  
Ronald E. McRoberts
Keyword(s):  
Remotely Sensed ◽  
National Forest Inventory ◽  
Data Types ◽  
Remotely Sensed Data ◽  
Large Area ◽  
Forest Inventories ◽  
Temporal Misalignment ◽  
Total Tree ◽  
Potential Efficiency ◽  
Post Stratification

Post-stratification is often used to increase the precision of estimates arising from large-area forest inventories with plots established at permanent locations. Remotely sensed data and associated spatial products are often used for developing the post-stratification, which offers a mechanism to increase precision for less cost than increasing the sample size. While important variance reductions have been shown from post-stratification, it remains unknown where observed gains lie along the continuum of possible gains. This information is needed to determine whether efforts to further improve post-stratification outcomes are warranted. In this study, two types of ‘optimal’ post-stratification were compared to typical production-based post-stratifications to estimate the magnitude of remaining gains possible. Although the ‘optimal’ post-stratifications were derived using methods inappropriate for operational usage, the results indicated that substantial further increases in precision for estimates of both forest area and total tree biomass could be obtained with better post-stratifications. The potential gains differed by the attribute being estimated, the population being studied, and the number of strata. Practitioners seeking to optimize post-stratification face challenges such as evaluation of numerous auxiliary data sources, temporal misalignment between plot observations and remotely sensed data acquisition, and spatial misalignment between plot locations and remotely sensed data due to positional errors in both data types.

scholarly journals Is the ‘Local Candidate’ Advantage a Myth? Analysing the Effects of Localism in the 2015 UK General Election

2016 ◽  
Author(s):  
Javier Sajuria
Keyword(s):  
Mediation Analysis ◽  
General Election ◽  
Data Sources ◽  
Election Study ◽  
Multilevel Regression ◽  
Factual Information ◽  
Diverse Range ◽  
Local Candidate ◽  
Post Stratification

This paper studies the question of the so-called electoral advantage of local candidates. We use a diverse range of data sources to estimate whether a candidate residing in the same constituency they compete has any advantage at all. We then compare the effect of the factual information against a measure of perception of residence, taken from the British Election Study Internet Panel. We propose different methodological innovations from traditional analyses of this issue. We first concentrate on the top two candidates of the most competitive constituencies, and use a measurement of perception calculates using Multilevel Regression with Post-stratification. We use mediation analysis to estimate the overall effects. Our findings show that local candidates have an advantage only if they are perceived as local, and that incumbents are usually perceived as more local than challengers.

The Use of E-Questionnaires in Organizational Surveys

2013 ◽  
pp. 1-23
Author(s):  
Yael Brender-Ilan ◽  
Gideon Vinitzky
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Human Resource ◽  
Principal Component ◽  
Point Of View ◽  
Future Research ◽  
Advantages And Disadvantages ◽  
Organizational Surveys ◽  
Exploratory Survey ◽  
Hr Managers

In recent years, there has been an increase in academic studies that examine the advantages and disadvantages of using e-questionnaires in organizations, but these studies have tended to ignore the potential differences between human resource (HR) managers and HR consultants with regards to using this tool. This chapter examines the use of e-questionnaires from the point of view of both types of practitioners. The study includes a qualitative exploratory survey, as well as a quantitative survey. T-tests, cluster analysis, and principal component analysis are performed and results support the three propositions that are presented. Specifically, it was found that (a) HR consultants and HR managers differ in the ranking of factors they think are important when deciding whether to use e-questionnaires; (b) preference differences exist between HR managers and HR consultants - managers are more directed by organizational constraints than consultants; and (c) the groupings for e-questionnaire preferences, compared to paper-and-pencil questionnaires, are consistent with Caldwell’s (2003) four roles of HR managers. The chapter concludes with implications and suggestions for future research.

Measuring Wages Worldwide

2013 ◽  
pp. 100-119 ◽  
Author(s):  
Stephanie Steinmetz ◽  
Damian Raess ◽  
Kea Tijdens ◽  
Pablo de Pedraza
Keyword(s):  
Developing Countries ◽  
Data Collection ◽  
Demographic Variables ◽  
Web Survey ◽  
Data Collection Tool ◽  
Individual Level ◽  
Estimated Parameters ◽  
The Difference ◽  
The Web ◽  
Post Stratification

This chapter discusses the potentials and constraints of using a volunteer Web survey as a worldwide data collection tool for wages. It provides a detailed description of the bias related to individual-level wages and core socio-demographic and employment-related variables across selected developed and developing countries and evaluates the efficiency of post-stratification weights in adjusting these biases. The results confirm that Web samples are particularly attractive to younger persons, part-timers, and persons working in non-manual occupations. This can be observed across countries, although the strength of the bias differs between them. With respect to the efficiency of post-stratification weights, the results are inconclusive. Whereas it is advisable to implement weights for descriptive purposes of socio-demographic variables, the contrary holds in case of wages. Additionally, weights can have the opposite effect by (moderately) increasing the difference in the estimated parameters between the reference and the Web sample.

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