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Title

Statistical analysis of observational studies in disability research.

Authors

Shepherd, Daisy A.; Amor, David J.; Moreno‐Betancur, Margarita

Abstract

Observational studies have a critical role in disability research, providing the opportunity to address a range of research questions. Over the past decades, there have been substantial shifts and developments in statistical methods for observational studies, most notably for causal inference. In this review, we provide an overview of modern design and analysis concepts critical for observational studies, drawing examples from the field of disability research and highlighting the challenges in this field, to inform the readership on important statistical considerations for their studies. What this paper adds: Descriptive research questions have specific analytical complexities, so careful statistical design before analysis is critical.Prediction research aims to produce a model with good predictive ability and requires thorough statistical design prior to analysis.Causal research requires careful statistical analysis planning, facilitated by modern causal inference concepts and analytical methods.Adopting these approaches will strengthen the quality of observational studies addressing a range of research questions in the disability space. What this paper adds: Descriptive research questions have specific analytical complexities, so careful statistical design before analysis is critical.Prediction research aims to produce a model with good predictive ability and requires thorough statistical design prior to analysis.Causal research requires careful statistical analysis planning, facilitated by modern causal inference concepts and analytical methods.Adopting these approaches will strengthen the quality of observational studies addressing a range of research questions in the disability space.

Subjects

RESEARCH questions; CAUSAL inference; EXPERIMENTAL design; SCIENTIFIC observation; DISABILITY studies

Publication

Developmental Medicine & Child Neurology, 2024, Vol 66, Issue 11, p1408

ISSN

0012-1622

Publication type

Academic Journal

DOI

10.1111/dmcn.15948

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