Skip to main navigation
Skip to search
Skip to main content
Tilburg University Research Portal Home
Help & FAQ
Home
Profiles
Research output
Research units
Activities
Projects
Press/Media
Prizes
Datasets
Search by expertise, name or affiliation
Latent class models for causal inference
F.J. Clouth
*
*
Corresponding author for this work
Methodology and Statistics
Research output
:
Thesis
›
Doctoral Thesis
185
Downloads (Pure)
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Latent class models for causal inference'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Mathematics
Confounding
100%
Causal Inference
100%
Causal Effect
80%
Exchangeability
80%
Probability Theory
60%
Auxiliary Variable
60%
Structural Model
40%
Treatment Group
40%
Confounders
40%
Direct Effect
40%
Parametric Model
20%
Longitudinal Data
20%
Inference Method
20%
Individual Patient
20%
Observational Data
20%
Latent Construct
20%
Retrospective Study
20%
Exp
20%
Causal Relationship
20%
Indicator Variable
20%
Keyphrases
Latent Class Analysis
100%
Causal Inference
100%
Latent Class Model
100%
Inverse Propensity Weighting
40%
Patient-Reported Outcomes Measurement Information System (PROMIS)
26%
Causal Effect
13%
Class Membership
13%
Exchangeability
13%
Confounding
10%
Invariance
10%
Auxiliary Variable
10%
Debiasing
10%
G-formula
10%
Social Sciences
6%
Latent Class
6%
Behavioral Sciences
6%
Measurement Model
6%
Treatment Group
6%
Engels
6%
Parametric Model
3%
Causal Relationship
3%
Latent Variables
3%
Dynamic Dependence
3%
Class-specific
3%
Separation Model
3%
Longitudinal Data
3%
Latent Markov Model
3%
Methoden
3%
Drie
3%
Clustering Methods
3%
Class-based
3%
Health-related Quality of Life
3%
Valid Measurements
3%
Cancer Survivors
3%
Treatment Conditions
3%
Observational Data
3%
Distal Outcome
3%
Maar
3%
Confounding Variables
3%
Indicator Variables
3%
Measure Data
3%
Specific Weight
3%
Measurement Noninvariance
3%
Latent Constructs
3%
Unobserved Classes
3%
Causal Inference Analysis
3%
Unsupervised Clustering
3%
Class Membership Probability
3%
Zero Probability
3%
Intermediate Confounding
3%
Categorical Exposures
3%
Nonexchangeable
3%
Arts and Humanities
Causal
100%
Class Analysis
100%
Propensity
43%
Categorical
6%
Social Sciences
6%
Positivity
6%
Behavioural Science
6%
Croon
6%
Technique
3%
Longitudinal Data
3%
Similarities
3%
Intermediate
3%
Survivors
3%
distal
3%
Engineering
Outcome Measure
100%
Auxiliary Variable
37%
Direct Effect
25%
Positivity
25%
Structural Model
25%
Observables
12%
Similarities
12%
Individual Patient
12%
Powerful Method
12%
Nonzero Probability
12%
Separate Analysis
12%
Earth and Planetary Sciences
Behavioural Science
100%
Crater
50%
Markov Model
50%
Biochemistry, Genetics and Molecular Biology
Retrospective Study
100%