Daniel Almirall
Biographic Data
| ID | 4168535 |
|---|---|
| NAME | Daniel Almirall |
| GIVEN NAMES | Daniel |
| FAMILY NAME | Almirall |
| SIGNATURE | ALMIRALL D |
| AFFILIATIONS | Institute for Social Research |
| ORCID | 0000-0002-9697-6600 |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 11 |
| WORKS AS AUTHOR | 6 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2009 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 1 |
SMART Binary
Sequential Multiple-Assignment Randomized Trials (SMARTs) play an increasingly important role in psychological and behavioral health research. This experimental approach enables researchers to answer scientific questions about how to sequence and match interventions to the unique, changing needs of individuals. A variety of sample size planning resources for SMART studies have been developed, enabling researchers to plan SMARTs for addressing dif…
A Data Analysis Method for Using Longitudinal Binary Outcome Data from a SMART to Compare Adaptive Interventions
Sequential multiple assignment randomized trials (SMARTs) are a useful and increasingly popular approach for gathering information to inform the construction of adaptive interventions to treat psychological and behavioral health conditions. Until recently, analysis methods for data from SMART designs considered only a single measurement of the outcome of interest when comparing the efficacy of adaptive interventions. Lu et al. proposed a method f…
Change in Patient Outcomes After Augmenting a Low-level Implementation Strategy in Community Practices That Are Slow to Adopt a Collaborative Chronic Care Model
BACKGROUND: Implementation strategies are essential for promoting the uptake of evidence-based practices and for patients to receive optimal care. Yet strategies differ substantially in their intensity and feasibility. Lower-intensity strategies (eg, training and technical support) are commonly used but may be insufficient for all clinics. Limited research has examined the comparative effectiveness of augmentations to low-level implementation str…
Estimating Moderated Causal Effects with Time-varying Treatments and Time-varying Moderators
Individuals differ in how they respond to a particular treatment or exposure, and social scientists are often interested in understanding how treatment effects are moderated by observed characteristics of individuals. Effect moderation occurs when individual covariates dampen or amplify the effect of some exposure. This article focuses on estimating moderated causal effects in longitudinal settings in which both the treatment and effect moderator…
A tutorial on propensity score estimation for multiple treatments using generalized boosted models
The use of propensity scores to control for pretreatment imbalances on observed variables in non‐randomized or observational studies examining the causal effects of treatments or interventions has become widespread over the past decade. For settings with two conditions of interest such as a treatment and a control, inverse probability of treatment weighted estimation with propensity scores estimated via boosted models has been shown in simulation…
Effects of two weight-loss diets on health-related quality of life
Estimating Moderated Causal Effects with Time-varying Treatments and Time-varying Moderators
Individuals differ in how they respond to a particular treatment or exposure, and social scientists are often interested in understanding how treatment effects are moderated by observed characteristics of individuals. Effect moderation occurs when individual covariates dampen or amplify the effect of some exposure. This article focuses on estimating moderated causal effects in longitudinal settings in which both the treatment and effect moderator…
Effects of two weight-loss diets on health-related quality of life
A tutorial on propensity score estimation for multiple treatments using generalized boosted models
The use of propensity scores to control for pretreatment imbalances on observed variables in non‐randomized or observational studies examining the causal effects of treatments or interventions has become widespread over the past decade. For settings with two conditions of interest such as a treatment and a control, inverse probability of treatment weighted estimation with propensity scores estimated via boosted models has been shown in simulation…
Estimating Moderated Causal Effects with Time-varying Treatments and Time-varying Moderators
Individuals differ in how they respond to a particular treatment or exposure, and social scientists are often interested in understanding how treatment effects are moderated by observed characteristics of individuals. Effect moderation occurs when individual covariates dampen or amplify the effect of some exposure. This article focuses on estimating moderated causal effects in longitudinal settings in which both the treatment and effect moderator…
A Data Analysis Method for Using Longitudinal Binary Outcome Data from a SMART to Compare Adaptive Interventions
Sequential multiple assignment randomized trials (SMARTs) are a useful and increasingly popular approach for gathering information to inform the construction of adaptive interventions to treat psychological and behavioral health conditions. Until recently, analysis methods for data from SMART designs considered only a single measurement of the outcome of interest when comparing the efficacy of adaptive interventions. Lu et al. proposed a method f…
Change in Patient Outcomes After Augmenting a Low-level Implementation Strategy in Community Practices That Are Slow to Adopt a Collaborative Chronic Care Model
BACKGROUND: Implementation strategies are essential for promoting the uptake of evidence-based practices and for patients to receive optimal care. Yet strategies differ substantially in their intensity and feasibility. Lower-intensity strategies (eg, training and technical support) are commonly used but may be insufficient for all clinics. Limited research has examined the comparative effectiveness of augmentations to low-level implementation str…
SMART Binary
Sequential Multiple-Assignment Randomized Trials (SMARTs) play an increasingly important role in psychological and behavioral health research. This experimental approach enables researchers to answer scientific questions about how to sequence and match interventions to the unique, changing needs of individuals. A variety of sample size planning resources for SMART studies have been developed, enabling researchers to plan SMARTs for addressing dif…
Advanced Causal Inference Techniques (4 works) · Mathematics (4 works) · Psychology (4 works) · Statistical Methods and Bayesian Inference (4 works) · Statistics (4 works) · Computer Science (3 works) · Medicine (3 works) · Psychiatry (3 works) · Binary number (2 works) · Econometrics (2 works)