The Graphic Analysis of Data

Parsonson, Barry S.; Baer, Donald M.

doi:10.1007/978-1-4684-8786-2_8

Cited by 94 publications

(79 citation statements)

References 19 publications

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“…Visual analysis has historically been considered appropriate and sufficient for longitudinal behavioral data analysis (Michael, 1974;Skinner, 1938) rendering statistical analysis necessary solely when enough experimental control is not achieved (Sidman, 1960). Complementarily, when only strong effects are sought for no further analysis seems to be required (Parsonson & Baer, 1986). Apart from identifying effective interventions, visual analysis has had a positive influence on scientific reports, given that it usually entails presenting the raw data gathered, which makes possible further analyses of these data, both visually (so that each analyst can reach his/her own decision) and statistically.…”

mentioning

confidence: 99%

A comparison of mean phase difference and generalized least squares for analyzing single-case data

Manolov

Solanas

2013

Journal of School Psychology

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The present study focuses on single-case data analysis and specifically on two procedures for quantifying differences between baseline and treatment measurementsThe first technique tested is based on generalized least squares regression analysis and is compared to a proposed non-regression technique, which allows obtaining similar information. The comparison is carried out in the context of generated data representing a variety of patterns (i.e., independent measurements, different serial dependence underlying processes, constant or phase-specific autocorrelation and data variability, different types of trend, and slope and level change). The results suggest that the two techniques perform adequately for a wide range of conditions and researchers can use both of them with certain guarantees. The regression-based procedure offers more efficient estimates, whereas the proposed non-regression procedure is more sensitive to intervention effects. Considering current and previous findings, some tentative recommendations are offered to applied researchers in order to help choosing among the plurality of single-case data analysis techniques.

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confidence: 99%

A comparison of mean phase difference and generalized least squares for analyzing single-case data

Manolov

Solanas

2013

Journal of School Psychology

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“…This provides a way to explore and index the consequences of assuming various degrees of autocorrelation. Other alternatives include visual analyses (Parsonson & Baer, 1986), effect sizes (Kromrey & Foster-Johnson, 1996), randomization tests (Edgington, 1980;Ferron & Sentovich, 2002;Koehler & Levin, 1998), integrated moving average (ARIMA) intervention models (Box & Tio, 1975), and a double bootstrap method (McKnight, McKean, & Huitema, 2000).…”

Section: Discussionmentioning

confidence: 99%

Reconsidering the use of the general linear model with single-case data

Ferron

2002

Behavior Research Methods, Instruments, & Computers

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“…Nonetheless, with the typical single-case data series lengths statistical procedures tend to have low power (e.g., Ferron & Ware, 1995), so this feature is not unique to the MRA. Moreover, if only strong interventions are assigned "small" p values, it is more likely that the effects of these interventions be of 36 practical (and not only statistical) significance, as was suggested also for visual analysis (Parsonson & Baer, 1986). In terms of the efforts required from the researcher, using the MRA involves only making a comparison to an already available maximal reference for the index and phase lengths used.…”

Section: Strengths and Limitations Of The Additional Evidence For Effmentioning

confidence: 99%