Dataset Information

Longitudinal analysis of pre- and post-treatment measurements with equal baseline assumptions in randomized trials.

ABSTRACT: For continuous variables of randomized controlled trials, recently, longitudinal analysis of pre- and posttreatment measurements as bivariate responses is one of analytical methods to compare two treatment groups. Under random allocation, means and variances of pretreatment measurements are expected to be equal between groups, but covariances and posttreatment variances are not. Under random allocation with unequal covariances and posttreatment variances, we compared asymptotic variances of the treatment effect estimators in three longitudinal models. The data-generating model has equal baseline means and variances, and unequal covariances and posttreatment variances. The model with equal baseline means and unequal variance-covariance matrices has a redundant parameter. In large sample sizes, these two models keep a nominal type I error rate and have high efficiency. The model with equal baseline means and equal variance-covariance matrices wrongly assumes equal covariances and posttreatment variances. Only under equal sample sizes, this model keeps a nominal type I error rate. This model has the same high efficiency with the data-generating model under equal sample sizes. In conclusion, longitudinal analysis with equal baseline means performed well in large sample sizes. We also compared asymptotic properties of longitudinal models with those of the analysis of covariance (ANCOVA) and t-test.

SUBMITTER: Funatogawa I

PROVIDER: S-EPMC7079084 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Longitudinal analysis of pre- and post-treatment measurements with equal baseline assumptions in randomized trials.

Funatogawa Ikuko I Funatogawa Takashi T

Biometrical journal. Biometrische Zeitschrift 20190808 2

For continuous variables of randomized controlled trials, recently, longitudinal analysis of pre- and posttreatment measurements as bivariate responses is one of analytical methods to compare two treatment groups. Under random allocation, means and variances of pretreatment measurements are expected to be equal between groups, but covariances and posttreatment variances are not. Under random allocation with unequal covariances and posttreatment variances, we compared asymptotic variances of the ...[more]

PMID: 31394012

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Project description:To fully assess the various dimensions affected by schizophrenia, clinical trials often include multiple scales measuring various symptom profiles, cognition, quality of life, subjective well-being, and functional impairment. In this exploratory study, we characterized the relationships among six clinical, functional, cognitive, and quality-of-life measures, identifying a parsimonious set of measurements.We used baseline data from a randomized, multicenter study of patients diagnosed with schizophrenia, schizoaffective disorder, or schizophreniform disorder who were experiencing an acute symptom exacerbation (n = 628) to examine the relationship among several outcome measures. These measures included the Positive and Negative Syndrome Scale (PANSS), Montgomery-Asberg Depression Rating Scale (MADRS), Brief Assessment of Cognition in Schizophrenia Symbol Coding Test, Subjective Well-being Under Neuroleptics Scale Short Form (SWN-K), Schizophrenia Objective Functioning Instrument (SOFI), and Quality of Life Scale (QLS). Three analytic approaches were used: 1) path analysis; 2) factor analysis; and 3) categorical latent variable analysis. In the optimal path model, the SWN-K was selected as the final outcome, while the SOFI mediated the effect of the exogenous variables (PANSS, MADRS) on the QLS.The overall model explained 47% of variance in QLS and 17% of the variance in SOFI, but only 15% in SWN-K. Factor analysis suggested four factors: "Functioning," "Daily Living," "Depression," and "Psychopathology." A strong positive correlation was observed between the SOFI and QLS (r = 0.669), and both the QLS and SOFI loaded on the "Functioning" factor, suggesting redundancy between these scales. The measurement profiles from the categorical latent variable analysis showed significant variation in functioning and quality of life despite similar levels of psychopathology.Researchers should consider collecting PANSS, SOFI, and SWN-K in their trials. This would allow a broad spectrum of assessments that would have the ability to capture a wide range of treatment outcomes and allow for a rich characterization of the subgroups involved. Additional research is needed to identify the critical cognitive measures.Predicting Response to Risperidone Treatment Through Identification of Early-onset of Antipsychotic Drug Action in SchizophreniaClinicalTrials.gov identifier: NCT00337662; http://www.clinicaltrials.gov/

Dataset Information

Longitudinal analysis of pre- and post-treatment measurements with equal baseline assumptions in randomized trials.

Publications

Longitudinal analysis of pre- and post-treatment measurements with equal baseline assumptions in randomized trials.

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