Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/32258
Title: Estimating slope and level change in N=1 designs
Author: Solanas Pérez, Antonio
Manolov, Rumen
Onghena, Patrick
Keywords: Investigació de cas únic
Investigació psicològica
Estadística
Single subject research
Psychological research
Statistics
Issue Date: 2010
Publisher: Sage Publications
Abstract: The current study proposes a new procedure for separately estimating slope change and level change between two adjacent phases in single-case designs. The procedure eliminates baseline trend from the whole data series prior to assessing treatment effectiveness. The steps necessary to obtain the estimates are presented in detail, explained, and illustrated. A simulation study is carried out to explore the bias and precision of the estimators and compare them to an analytical procedure matching the data simulation model. The experimental conditions include two data generation models, several degrees of serial dependence, trend, level and/or slope change. The results suggest that the level and slope change estimates provided by the procedure are unbiased for all levels of serial dependence tested and trend is effectively controlled for. The efficiency of the slope change estimator is acceptable, whereas the variance of the level change estimator may be problematic for highly negatively autocorrelated data series.
Note: Versió postprint del document publicat a: http://dx.doi.org/10.1177/0145445510363306
It is part of: Behavior Modification, 2010, vol. 34, num. 3, p. 195-218
Related resource: http://dx.doi.org/10.1177/0145445510363306
URI: http://hdl.handle.net/2445/32258
ISSN: 0145-4455
Appears in Collections:Articles publicats en revistes (Psicologia Social i Psicologia Quantitativa)

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