General location multivariate latent variable models for mixed correlated bounded continuous, ordinal, and nominal responses with non-ignorable missing data
© 2020 Informa UK Limited, trading as Taylor & Francis Group..
Using a multivariate latent variable approach, this article proposes some new general models to analyze the correlated bounded continuous and categorical (nominal or/and ordinal) responses with and without non-ignorable missing values. First, we discuss regression methods for jointly analyzing continuous, nominal, and ordinal responses that we motivated by analyzing data from studies of toxicity development. Second, using the beta and Dirichlet distributions, we extend the models so that some bounded continuous responses are replaced for continuous responses. The joint distribution of the bounded continuous, nominal and ordinal variables is decomposed into a marginal multinomial distribution for the nominal variable and a conditional multivariate joint distribution for the bounded continuous and ordinal variables given the nominal variable. We estimate the regression parameters under the new general location models using the maximum-likelihood method. Sensitivity analysis is also performed to study the influence of small perturbations of the parameters of the missing mechanisms of the model on the maximal normal curvature. The proposed models are applied to two data sets: BMI, Steatosis and Osteoporosis data and Tehran household expenditure budgets.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2021 |
|---|---|
| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:48 |
|---|---|
| Enthalten in: |
Journal of applied statistics - 48(2021), 5 vom: 09., Seite 765-785 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Tabrizi, Elham [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
62J05 |
|---|
| Anmerkungen: |
Date Revised 16.07.2022 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
|---|
| doi: |
10.1080/02664763.2020.1745765 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM342288350 |
|---|
| LEADER | 01000naa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM342288350 | ||
| 003 | DE-627 | ||
| 005 | 20231226013745.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231226s2021 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1080/02664763.2020.1745765 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1140.xml |
| 035 | |a (DE-627)NLM342288350 | ||
| 035 | |a (NLM)35707447 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Tabrizi, Elham |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a General location multivariate latent variable models for mixed correlated bounded continuous, ordinal, and nominal responses with non-ignorable missing data |
| 264 | 1 | |c 2021 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Revised 16.07.2022 | ||
| 500 | |a published: Electronic-eCollection | ||
| 500 | |a Citation Status PubMed-not-MEDLINE | ||
| 520 | |a © 2020 Informa UK Limited, trading as Taylor & Francis Group. | ||
| 520 | |a Using a multivariate latent variable approach, this article proposes some new general models to analyze the correlated bounded continuous and categorical (nominal or/and ordinal) responses with and without non-ignorable missing values. First, we discuss regression methods for jointly analyzing continuous, nominal, and ordinal responses that we motivated by analyzing data from studies of toxicity development. Second, using the beta and Dirichlet distributions, we extend the models so that some bounded continuous responses are replaced for continuous responses. The joint distribution of the bounded continuous, nominal and ordinal variables is decomposed into a marginal multinomial distribution for the nominal variable and a conditional multivariate joint distribution for the bounded continuous and ordinal variables given the nominal variable. We estimate the regression parameters under the new general location models using the maximum-likelihood method. Sensitivity analysis is also performed to study the influence of small perturbations of the parameters of the missing mechanisms of the model on the maximal normal curvature. The proposed models are applied to two data sets: BMI, Steatosis and Osteoporosis data and Tehran household expenditure budgets | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a 62J05 | |
| 650 | 4 | |a 62J12 | |
| 650 | 4 | |a Beta regression | |
| 650 | 4 | |a conditional grouped continuous model | |
| 650 | 4 | |a general mixed data model | |
| 650 | 4 | |a latent variable | |
| 650 | 4 | |a the maximal normal curvature | |
| 700 | 1 | |a Bahrami Samani, Ehsan |e verfasserin |4 aut | |
| 700 | 1 | |a Ganjali, Mojtaba |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Journal of applied statistics |d 1991 |g 48(2021), 5 vom: 09., Seite 765-785 |w (DE-627)NLM098188178 |x 0266-4763 |7 nnns |
| 773 | 1 | 8 | |g volume:48 |g year:2021 |g number:5 |g day:09 |g pages:765-785 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1080/02664763.2020.1745765 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 48 |j 2021 |e 5 |b 09 |h 765-785 | ||