W F Velicer
Overview
Explore the profile of W F Velicer including associated specialties, affiliations and a list of published articles.
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72
Citations
5588
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Recent Articles
1.
Velicer W, McDonald R
Multivariate Behav Res
. 2016 Feb;
26(2):247-54.
PMID: 26828253
Cross-sectional time series designs assess the generalizability of intervention effects across different units. The general transformation approach to time series analysis was proposed by Velicer and McDonald (1984) to avoid...
2.
Zwick W, Velicer W
Multivariate Behav Res
. 2016 Jan;
17(2):253-69.
PMID: 26810950
The performance of four rules for determining the number of components to retain (Kaiser's eigenvalue greater than unity, Cattell's SCREE, Bartlett's test, and Velicer's MAP) was investigated across four systematically...
3.
Velicer W
Multivariate Behav Res
. 2016 Jan;
12(1):3-22.
PMID: 26804141
Factor analysis, image component analysis, and principal component analysis are three methods that have been employed for the same purpose. Factor analysis was traditionally viewed as the preferred method, with...
4.
Velicer W, Peacock A, Jackson D
Multivariate Behav Res
. 2016 Jan;
17(3):371-88.
PMID: 26800757
Factor analysis and component analysis represent two broad classes of methods employed generally with similar types of problems. The purpose of the present study is to determine the extent to...
5.
Harrop J, Velicer W
Multivariate Behav Res
. 2016 Jan;
25(2):233-48.
PMID: 26794488
Interrupted time series analysis involves repeated observations on a single unit both preceding and following an intervention. Recently developed statistical procedures permit inferential statements about the degree and pattern of...
6.
Harrop J, Velicer W
Multivariate Behav Res
. 2016 Jan;
25(2):219-31.
PMID: 26794487
Interrupted time series analysis is a method of analysis for longitudinal experiments involving a sequence of observations on a single dependent variable before and after an intervention. The presence of...
7.
Fava J, Velicer W
Multivariate Behav Res
. 2016 Jan;
27(3):387-415.
PMID: 26789789
The effects of overextracting factors and components within and between the methods of maximum likelihood factor analysis (MLFA) and principal component analysis (PCA) were examined. Computer-simulated data sets were generated...
8.
Fava J, Velicer W
Multivariate Behav Res
. 2016 Jan;
27(3):301-22.
PMID: 26789785
No abstract available.
9.
Prochaska J, Velicer W, Guadagnoli E, Rossi J, DiClemente C
Multivariate Behav Res
. 2016 Jan;
26(1):83-107.
PMID: 26782613
Patterns of change occurring in a combined cross-sectional and longitudinal (cross-sequential) analysis of 14 variables were investigated in a two-year study of self-change approaches to smoking cessation. Every six months...
10.
Velicer W, Fava J
Multivariate Behav Res
. 2016 Jan;
22(2):193-209.
PMID: 26782065
An attribution of a latent variable procedure, such as factor analysis, that is sometimes cited is superior generalization from the variables sampled to the population of variables. Principal component analysis,...