Continuous Predictors of Pretest-Posttest Change: Highlighting the Impact of the Regression Artifact

Farmus, Linda; Arpin-Cribbie, Chantal A.; Cribbie, Robert A.

doi:10.3389/fams.2018.00064

Cited by 27 publications

(25 citation statements)

References 26 publications

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“…A fifth caveat is that adjusting baseline symptoms has been debated; future research may use different methods (e.g., latent variable modeling) to examine relations of loss-centrality subgroups with outcomes (cf. Farmus et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

The centrality of a loss-event: Patterns, correlates, and predictive value

Boelen

2021

Anxiety, Stress, & Coping

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Background and objectives: Evidence shows that the centrality of a lossevent maintains emotional distress following loss. Aims of the current study were to examine (i) if subgroups of bereaved people can be distinguished based on their endorsement of different manifestations of loss-centrality, (ii) if subgroup membership was associated with socio-demographic and loss-related variables, and (iii) the linkage of subgroup membership with symptom-levels of prolonged grief (PG), posttraumatic stress (PTS), and depression assessed concurrently and 6 months later. Methods: Three-hundred ninety-eight bereaved people completed the 7item Centrality of Event Scale, with their loss as anchor-event and completed symptom-measures concurrently and 6 months later. Latent profile analysis (LPA) was used to identity profiles of loss-centrality. Results: LPA revealed a three-profile solution representing low, average, and high centrality classes, respectively. The death of a partner and younger age increased the likelihood of membership of classes evidencing stronger centrality. Membership of the low centrality class was associated with lower concurrent PG, PTS, and depression; membership of the high centrality class predicted elevated PG 6 months later, beyond baseline PG. Conclusions: Subgroups of loss-centrality were distinguished by increasing endorsement of all (rather than some) manifestations of loss-centrality. Clinical implications are discussed.

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Section: Discussionmentioning

confidence: 99%

The centrality of a loss-event: Patterns, correlates, and predictive value

Boelen

2021

Anxiety, Stress, & Coping

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“…While a large body of evidence has addressed the change score approach vs. the t2 conditioning on time 1 differences (e.g., Castro-Schilo & Grimm, 2018;Farmus, Arpin-Cribbie, & Cribbie, 2019;Maris, 1998;O'Neill, Kreif, Grieve, Sutton, & Sekhon, 2016;Pearl, 2016;van Breukelen, 2013), the specific effects of retesting on t2 scores and other analytic techniques involving latent variable modeling have been relatively neglected. We extend the literature by showing how retest effects on test scores, but not on the underlying ability, can show up in every manifest score analysis-misleading researchers.…”

Section: Discussionmentioning

confidence: 99%

What to do Without a Control Group: You have to go latent, but not all latents are equal

Protzko¹,

Nijenhuis²,

Ziada³

et al. 2021

Preprint

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The One-Group Pretest-Posttest Design, where the same group of people is measured before and after some event, can be fraught with statistical problems and issues with causal inference. Still, these designs are common from political science to developmental neuropsychology to economics. In cases with cognitive data, it has long been known that a second test, with no treatment or an ineffective manipulation between testings, leads to increased scores at time 2 without an increase in the underlying latent ability. We investigate several analytic approaches involving both manifest and latent variable modeling to see which methods are able to accurately model manifest score changes with no latent change. Using data from 600 schoolchildren given an intelligence test twice, with no intervention between, we show using manifest test scores, either directly or through univariate latent change score analysis, falsely leads one to believe an underlying increase has occurred. Latent change score models on latent data also show a spurious significant effect on the underlying latent ability. Multigroup Confirmatory Factor Analysis only shows the correct answer when measurement invariance is tested, imposed (if viable), and the means of both time points are tested constricting time 2 to zero. Longitudinal structural equation modeling with measurement invariance correctly shows no change at the latent level when measurement invariance is tested, imposed, and model fit tested. When dealing with the One-Group Pretest-Posttest Design, analyses must occur at the latent level, measurement invariance tested, and change parameters explicitly tested. Otherwise, one may see change where none exists.

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“…Although there are some concerns that change scores are inherently unreliable, it has been demonstrated that this arises in rare and unusual circumstances (Rogosa & Willett, 1983; Trafimow, 2015). Furthermore, alternative approaches of employing statistical control of pre-treatment covariates is not recommended in the presence of a relationship between the pre-treatment variables and predictors, as it may result in increased Type I errors (Eriksson & Häggström, 2014; Farmus et al, 2019). In this study, there were low to moderate levels of correlations between the pre-treatment outcome measures and the predictors ( r = 0.09–0.52) rendering the implementation of change scores as the most appropriate statistical approach.…”

Section: Discussionmentioning

confidence: 99%

Clinical and parental predictors of emotion regulation following cognitive behaviour therapy in children with autism

Tajik-Parvinchi

Farmus

Cribbie

et al. 2020

Autism

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Difficulties with emotion regulation are common in children with autism. Although interventions targeting emotion regulation show promise, children’s individual treatment responses vary, and it is important to understand the factors that contribute to treatment change. The present study aimed to identify pre-treatment child characteristics and parent psychopathology that predict treatment response in a 10-week manualized cognitive behaviour therapy intervention for children with autism, 8–12 years of age. Exploratory best-subset regression analyses were first carried out to identify the optimal set of predictors. Logistic regressions were then conducted to determine whether these variables predicted reliable improvement. Outcome variables consisted of the lability/negativity and the emotion regulation subscales of the Emotion Regulation Checklist. Predictors included pre-treatment developmental, clinical, and parent psychopathology variables. Analyses revealed that youth who started the treatment with higher verbal reasoning, higher impairment in social motivation, and more anxious parents were more likely to show reliable improvements in emotion regulation. Youth who started the treatment with higher internalizing scores had lower odds of showing reliable improvement. Implications of our findings include facilitation of active involvement, avoidance of complex language, and the provision of additional supports. Further suggestions to inform clinical practice are discussed. Lay abstract Children with autism commonly experience difficulty controlling their emotions. Although existing treatments are successful in teaching critical emotion regulation skills, not all children improve. It is important to identify the factors that influence treatment response to be able to reach more children. This study aimed to identify child and parent characteristics that predict treatment response in a 10-week cognitive behaviour therapy treatment for children with autism, 8–12 years of age, and their parents. We found that youth who started the treatment with higher verbal abilities, who were more anxious in social situations, and had parents who were more anxious, were more likely to improve in learning new emotion regulation skills. We also found that children who had more physical discomforts or complaints before starting the treatment were less likely to improve in their negative expressions of emotion. Our study suggests that it is important for clinicians to promote active involvement and learning by avoiding complex language and to use more visual materials to supplement the learning process, and make sure that sessions are sensitive to the individual needs of participants.

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Continuous Predictors of Pretest-Posttest Change: Highlighting the Impact of the Regression Artifact

Cited by 27 publications

References 26 publications

The centrality of a loss-event: Patterns, correlates, and predictive value

The centrality of a loss-event: Patterns, correlates, and predictive value

What to do Without a Control Group: You have to go latent, but not all latents are equal

Clinical and parental predictors of emotion regulation following cognitive behaviour therapy in children with autism

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