Application of a Mixed Model Approach for Assessment of Interventions and Evaluation of Programs
Bibliographic Data
| ID | 13660767 |
|---|---|
| Authors | Guillermo Vallejo (0000-0002-8010-6854, Universidad de Oviedo, corresponding author), José Ramón Fernández (0000-0001-9801-7043, Universidad de Oviedo), Roberto Secades‐villa (0000-0001-8106-6594, Universidad de Oviedo), R Secades (Universidad de Oviedo) |
| Year | 2004 |
| Volume | 95 |
| Issue | 3_suppl |
| Pages | 1095-1118 |
| Publication date | 2004-12-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Psychological Reports (JOURNAL) |
| Journal identifiers | ISSN: 0033-2941 • E-ISSN: 1558-691X |
| Publisher | SAGE Publishing (PUBLISHER • US) |
| DOI | 10.2466/pr0.95.3f.1095-1118 |
| PMID | 15762391 |
| OpenAlex | W2107868218 |
| Language | EN |
| Citations received | 1 |
| References cited | 19 |
Many social programs and programs for prevention of drug use are designed to affect a wide variety of targets, including individuals, families and neighborhoods, and organizations such as schools, companies, or hospitals. The nature of the intervention and the design of the particular study determine the choice of the appropriate unit of analysis in assessments of outcome. When the units of assignment and units of observation differ from one another, that is, when clusters of persons rather than persons are assigned at random to treatments, analyses performed at lower levels in the study hierarchy provide inefficient estimates of parameters and often lead to inappropriate significance tests. The present goal was to illustrate the applications of linear mixed models for evaluating statistically the effectiveness of programs
Affect (linguistics · Hierarchy · Intervention (counseling · Management science · Mathematics education · Outcome (game theory · Psychiatry · Psychological intervention · Random assignment · Statistics · Unit (ring theory · Variety (cybernetics · Advanced Causal Inference Techniques · Applied Psychology · Artificial Intelligence · Behavioral and Psychological Studies · Computer Science · Engineering · Mathematics · Psychology · Statistical Methods and Bayesian Inference
Statistical power and optimal design for multisite randomized trials.
Random-Effects Models for Longitudinal Data
Statistical analysis and optimal design for cluster randomized trials.
Statistical Modelling Issues in School Effectiveness Studies
Using SAS PROC Mixed to Fit Multilevel Models, Hierarchical Models, and Individual Growth Models
Using SAS PROC Mixed to Fit Multilevel Models, Hierarchical Models, and Individual Growth Models
Hierarchical linear models
Multilevel Models and Unbiased Tests for Group Based Interventions
Multilevel Modeling of Individual and Group Level Mediated Effects
| Unique citing works | 1 |
|---|---|
| Citations per year | 0,06 |
| Citation span | 2008 - 2008 (1) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 1 |