Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Estimating a treatment effect from multidimensional longitudinal data.

Biometrics - 1 Sept 1998

Gray S M, Brookmeyer R

Abstract excerpt

Multidimensional longitudinal data result when researchers measure an outcome through time that is quantified by many different response variables. These response variables are often defined on different numerical scales. The objective of this paper is to present a method to summarize and estimate an overall treatment effect from this type of longitudinal data. A regression model is proposed that assumes the...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Acquired Immunodeficiency Syndrome
Share to Alleles
Share to Alzheimer Disease

Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

Share to Apolipoproteins E

Share to Longitudinal Studies

Share to Models, Statistical

Share to Regression Analysis

Share to Treatment Outcome

Source

Identifiers

PMID: 9750246

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence. Graph snapshot: 2026-09-29.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Estimating a treatment effect from multidimensional longitudinal data.PMID 9750246Read ↗

ShinyEvents: harmonizing longitudinal data for real world survival estimationSemantic proximity Read ↗

Non-Monotone Exponential Time (NEXT) Model for the Longitudinal Trend of a Continuous Outcome in Clinical TrialsSemantic proximity Read ↗

Repeated measures ASCA+ for analysis of longitudinal intervention studies with multivariate outcome dataSemantic proximity Read ↗

Exact conditional inference in models for longitudinal designsSemantic proximity Read ↗

When scalar endpoints cannot identify multidomain stabilization: estimand-aligned trajectory summaries for chronic longitudinal trialsSemantic proximity Read ↗

Application of Causal Inference Methods to Pooled Longitudinal Non- Randomized Studies: A Methodological Systematic ReviewSemantic proximity Read ↗

Uncovering general, shared, and unique temporal patterns in ambulatory assessment dataSemantic proximity Read ↗

Visualization of Incrementally Learned Projection Trajectories for Longitudinal DataSemantic proximity Read ↗

Advancing Predictive Modeling in Behavioral Health with Gradient Boosted Bootstrap ModelSemantic proximity Read ↗

Testing measurement invariance in a conditional likelihood framework by considering multiple covariates simultaneouslySemantic proximity Read ↗

Average Treatment Effects on Binary Outcomes with Stochastic CovariatesSemantic proximity Read ↗

Between-Case Standardized Mean Differences: Flexible Methods for Single-Case DesignsSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.