Unions’ Use of Attitude Surveys

2019 ◽  
Vol 42 (2) ◽  
pp. 7-8
Keyword(s):  
2012 ◽  
Author(s):  
Christopher Lake ◽  
Scott A. Withrow ◽  
Nicole L. Wood ◽  
Joseph J. Bochinski ◽  
Dev K. Dalal ◽  
...  
Keyword(s):  

2009 ◽  
Author(s):  
Karsten Mueller ◽  
Natascha Hausmann ◽  
Tammo Straatmann ◽  
Keith Hattrup

1976 ◽  
Vol 54 (1) ◽  
pp. 40-42
Author(s):  
David A. Lyman ◽  
Clemm C. Kessler
Keyword(s):  

2000 ◽  
Vol 85 (2) ◽  
pp. 284-293 ◽  
Author(s):  
Steven G. Rogelberg ◽  
Alexandra Luong ◽  
Matthew E. Sederburg ◽  
Dean S. Cristol

2009 ◽  
Vol 12 (3) ◽  
pp. 260-278 ◽  
Author(s):  
Keith Walley ◽  
Paul Custance ◽  
Gaynor Orton ◽  
Stephen Parsons ◽  
Adam Lindgreen ◽  
...  

2018 ◽  
Vol 49 (1) ◽  
pp. 250-276 ◽  
Author(s):  
Maria Iannario ◽  
Marica Manisera ◽  
Domenico Piccolo ◽  
Paola Zuccolotto

In analyzing data from attitude surveys, it is common to consider the “don’t know” responses as missing values. In this article, we present a statistical model commonly used for the analysis of responses/evaluations expressed on Likert scales and extended to take into account the presence of don’t know responses. The main objective is to offer an alternative to the usual custom to treat them as missing values by considering them as a source of uncertainty. The original proposal in this article is the introduction of the relevant covariates in order to discriminate subpopulations that can show different behaviors in choosing between a substantive response and the don’t know option.


Sign in / Sign up

Export Citation Format

Share Document