Tabea Rosenkranz
Datos Biográficos
| ID | 5705654 |
|---|---|
| NOMBRE | Tabea Rosenkranz |
| NOMBRES | Tabea |
| APELLIDO | Rosenkranz |
| FIRMA | ROSENKRANZ T |
| AFILIACIONES | Ludwig-Maximilians-Universität München |
| ORCID | 0000-0001-6071-9357 |
| VERIFICADO | Sí |
| TOTAL DE OBRAS | 3 |
| TOTAL DE CITAS | 0 |
| OBRAS COMO AUTOR | 3 |
| OBRAS COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 2014 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 2025 |
| ÍNDICE H | 0 |
Early Improvement Predicts Treatment Response in Depression
Predicting treatment response through early improvement can reduce patients' time in ineffective treatments before considering alternatives. However, for psychological interventions, there is no consensus on what time window and improvement rate early in the treatment is the most informative for distinguishing treatment responders from nonresponders. This study investigated these aspects in an inpatient and day clinic setting among severe depress…
Clustering Individuals on Limited Features of a Vector Autoregressive Model
Dynamical interplays in emotions have been investigated using vector autoregressive (VAR) models, whose estimates can be used to cluster participants into unknown groups. The present study evaluated a clustering algorithm, the alternating least square (ALS) algorithm, for accuracy in predicting individual group membership. We systematically manipulated (a) the number of variables in a model, (b) the size of group differences in regression coeffic…
Measuring Somatic Complaints in Primary School Children
Sin obras prominentes en esta página.
Measuring Somatic Complaints in Primary School Children
Clustering Individuals on Limited Features of a Vector Autoregressive Model
Dynamical interplays in emotions have been investigated using vector autoregressive (VAR) models, whose estimates can be used to cluster participants into unknown groups. The present study evaluated a clustering algorithm, the alternating least square (ALS) algorithm, for accuracy in predicting individual group membership. We systematically manipulated (a) the number of variables in a model, (b) the size of group differences in regression coeffic…
Early Improvement Predicts Treatment Response in Depression
Predicting treatment response through early improvement can reduce patients' time in ineffective treatments before considering alternatives. However, for psychological interventions, there is no consensus on what time window and improvement rate early in the treatment is the most informative for distinguishing treatment responders from nonresponders. This study investigated these aspects in an inpatient and day clinic setting among severe depress…
Child and Adolescent Psychosocial and Emotional Development (2 obras) · Clinical Psychology (2 obras) · Mental Health Research Topics (2 obras) · Psychiatry (2 obras) · Psychology (2 obras) · Algorithm (1 obra) · Artificial Intelligence (1 obra) · Artificial Intelligence (1 obra) · Autoregressive model (1 obra) · Behavioral Health and Interventions (1 obra)