Mixed location scale hidden Markov model for the analysis of intensive longitudinal data

Hidden Markov models (HMM) presents an attractive analytical framework for capturing the state-switching process for auto-correlated data. These models have been extended to longitudinal data setting where simultaneous multiple processes are observed by including subject specific random effects. How...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Health services and outcomes research methodology Ročník 20; číslo 4; s. 222 - 236
Hlavní autoři: Lin, Xiaolei, Mermelstein, Robin, Hedeker, Donald
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.12.2020
Springer Nature B.V
Témata:
Behavior
Data compression
Economics
Health Administration
Health services
Latent class analysis
Longitudinal studies
Markov analysis
Medicine
Medicine & Public Health
Methodology of the Social Sciences
Probability
Public Health
Research methodology
Statistics
Teenagers
Mixed effect models
Intensive longitudinal data
Latent class classification
ISSN:1387-3741, 1572-9400
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Abstract Hidden Markov models (HMM) presents an attractive analytical framework for capturing the state-switching process for auto-correlated data. These models have been extended to longitudinal data setting where simultaneous multiple processes are observed by including subject specific random effects. However, application of HMMs for intensive longitudinal data, where each subject gets measured intensively over relatively short period of time, has not been widely studied. In this paper, we extend the mixed hidden Markov model and allow subject heterogeneity with respect to the mean and within subject variance by including subject random effects in both perspectives. We focus on the application of this model to intensive longitudinal studies in psychological and behavioral research where individual’s latent states and state-switching process are of interest. Models are estimated using forward–backward algorithm via Bayesian sampling approach. Advantages over regular HMM and mixed HMM that only accounts for the subjects’ mean heterogeneity are illustrated through a series of simulation studies. Finally, models are applied to an adolescent mood study data set and results show that the proposed mixed location scale HMM achieves better model fit and more interpretative mood state identification in terms of state specific covariate effects compared to regular HMM and mixed HMM.
AbstractList Hidden Markov models (HMM) presents an attractive analytical framework for capturing the state-switching process for auto-correlated data. These models have been extended to longitudinal data setting where simultaneous multiple processes are observed by including subject specific random effects. However, application of HMMs for intensive longitudinal data, where each subject gets measured intensively over relatively short period of time, has not been widely studied. In this paper, we extend the mixed hidden Markov model and allow subject heterogeneity with respect to the mean and within subject variance by including subject random effects in both perspectives. We focus on the application of this model to intensive longitudinal studies in psychological and behavioral research where individual’s latent states and state-switching process are of interest. Models are estimated using forward–backward algorithm via Bayesian sampling approach. Advantages over regular HMM and mixed HMM that only accounts for the subjects’ mean heterogeneity are illustrated through a series of simulation studies. Finally, models are applied to an adolescent mood study data set and results show that the proposed mixed location scale HMM achieves better model fit and more interpretative mood state identification in terms of state specific covariate effects compared to regular HMM and mixed HMM.
Author Lin, Xiaolei
Hedeker, Donald
Mermelstein, Robin
Author_xml – sequence: 1
  givenname: Xiaolei
  orcidid: 0000-0003-2463-1272
  surname: Lin
  fullname: Lin, Xiaolei
  email: xiaoleilin@fudan.edu.cn
  organization: Fudan University
– sequence: 2
  givenname: Robin
  surname: Mermelstein
  fullname: Mermelstein, Robin
  organization: University of Illinois at Chicago
– sequence: 3
  givenname: Donald
  surname: Hedeker
  fullname: Hedeker, Donald
  organization: University of Chicago
BookMark eNp9kE1LAzEQhoNUsK3-AU8Bz6v52N1kj1L8ghYvCt5C3My2qdukJmmx_97YCoKHnmZg3mdmeEZo4LwDhC4puaaEiJtIiShZQRgpCGFUFNUJGtJKsKIpCRnknktRcFHSMzSKcZlDjNRyiN5m9gsM7n2rk_UOx1b3gBfWGHB4psOH3-KVN9DjzgecFoC10_0u2oh9h61L4KLdQl7g5jZtjM1TbHTS5-i0032Ei986Rq_3dy-Tx2L6_PA0uZ0WLadNKkrJayYMr0BQkMbIGqistSb1e8VJQ5khEkCWGlrghjZNV3EjpKlkx8uy7vgYXR32roP_3EBMauk3IX8RFauJrBmjvMwpdki1wccYoFPrYFc67BQl6segOhhU2aDaG1RVhuQ_qLVprykFbfvjKD-gMd9xcwh_Xx2hvgEpIYcf
CitedBy_id crossref_primary_10_1080_00273171_2023_2205392
crossref_primary_10_1007_s10742_021_00240_0
crossref_primary_10_1061_JSWBAY_SWENG_632
Cites_doi 10.1007/s11222-016-9696-4
10.1198/016214506000001086
10.1177/0962280217706728
10.1002/sim.7627
10.1111/j.1541-0420.2007.00924.x
10.3102/1076998614546494
10.1007/s10742-018-0184-5
10.1037/a0016276
10.1146/annurev.clinpsy.3.022806.091415
10.1214/09-AOAS282
10.1097/PSY.0b013e31825474cb
10.1037/adb0000165
10.1080/00273171.2012.658328
10.1198/jcgs.2011.09109
10.1016/S1672-0229(04)02014-5
10.1142/S0218001401000836
10.1214/14-AOAS765
10.1093/abm/16.3.199
10.1561/2000000004
10.1080/00273171.2017.1370364
ContentType Journal Article
Copyright Springer Science+Business Media, LLC, part of Springer Nature 2020
Springer Science+Business Media, LLC, part of Springer Nature 2020.
Copyright_xml – notice: Springer Science+Business Media, LLC, part of Springer Nature 2020
– notice: Springer Science+Business Media, LLC, part of Springer Nature 2020.
DBID AAYXX
CITATION
3V.
7WY
7WZ
7X7
7XB
87Z
88C
8AO
8FI
8FJ
8FK
8FL
ABUWG
AFKRA
BENPR
BEZIV
CCPQU
DWQXO
FRNLG
FYUFA
F~G
GHDGH
K60
K6~
K9.
L.-
M0C
M0S
M0T
PHGZM
PHGZT
PJZUB
PKEHL
PPXIY
PQBIZ
PQBZA
PQEST
PQQKQ
PQUKI
PYYUZ
Q9U
DOI 10.1007/s10742-020-00217-5
DatabaseName CrossRef
ProQuest Central (Corporate)
ABI/INFORM Collection
ABI/INFORM Global (PDF only)
ProQuest Health & Medical Collection
ProQuest Central (purchase pre-March 2016)
ABI/INFORM Collection
Healthcare Administration Database (Alumni)
ProQuest Pharma Collection
ProQuest Hospital Collection
Hospital Premium Collection (Alumni Edition)
ProQuest Central (Alumni) (purchase pre-March 2016)
ABI/INFORM Collection (Alumni)
ProQuest Central (Alumni)
ProQuest Central UK/Ireland
ProQuest Central
Business Premium Collection
ProQuest One Community College
ProQuest Central
Business Premium Collection (Alumni)
Health Research Premium Collection
ABI/INFORM Global (Corporate)
Health Research Premium Collection (Alumni)
ProQuest Business Collection (Alumni Edition)
ProQuest Business Collection
ProQuest Health & Medical Complete (Alumni)
ABI/INFORM Professional Advanced
ProQuest ABI/INFORM Global
ProQuest Health & Medical Collection
Healthcare Administration Database
ProQuest Central Premium
ProQuest One Academic (New)
ProQuest Health & Medical Research Collection
ProQuest One Academic Middle East (New)
One Health & Nursing
ProQuest One Business (OCUL)
ProQuest One Business (Alumni)
ProQuest One Academic Eastern Edition (DO NOT USE)
ProQuest One Academic (retired)
ProQuest One Academic UKI Edition
ABI/INFORM Collection China
ProQuest Central Basic
DatabaseTitle CrossRef
ABI/INFORM Global (Corporate)
ProQuest Business Collection (Alumni Edition)
ProQuest One Business
ProQuest One Academic Middle East (New)
ProQuest Health & Medical Complete (Alumni)
ProQuest Central (Alumni Edition)
ProQuest One Community College
ProQuest One Health & Nursing
ProQuest Pharma Collection
ABI/INFORM Complete
ProQuest Central
ABI/INFORM Professional Advanced
ProQuest Health & Medical Research Collection
Health Research Premium Collection
Health and Medicine Complete (Alumni Edition)
ProQuest Central Korea
Health & Medical Research Collection
ProQuest Central (New)
ABI/INFORM Complete (Alumni Edition)
Business Premium Collection
ABI/INFORM Global
ABI/INFORM Global (Alumni Edition)
ProQuest Central Basic
ProQuest One Academic Eastern Edition
ProQuest Health Management
ABI/INFORM China
ProQuest Hospital Collection
Health Research Premium Collection (Alumni)
ProQuest Business Collection
ProQuest Hospital Collection (Alumni)
ProQuest Health & Medical Complete
ProQuest One Academic UKI Edition
ProQuest Health Management (Alumni Edition)
ProQuest One Business (Alumni)
ProQuest One Academic
ProQuest One Academic (New)
ProQuest Central (Alumni)
Business Premium Collection (Alumni)
DatabaseTitleList ABI/INFORM Global (Corporate)
Database_xml – sequence: 1
  dbid: M0T
  name: Healthcare Administration Database
  url: https://search.proquest.com/healthmanagement
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Discipline Medicine
Economics
Public Health
Statistics
EISSN 1572-9400
EndPage 236
ExternalDocumentID 10_1007_s10742_020_00217_5
GrantInformation_xml – fundername: Science and Technology Commission of Shanghai Municipality
  grantid: 19YF1402900
  funderid: http://dx.doi.org/10.13039/501100003399
GroupedDBID ---
-5E
-5G
-BR
-EM
-Y2
-~C
.86
.VR
06D
0R~
0VY
1N0
1SB
203
29I
29~
2J2
2JN
2JY
2KG
2KM
2LR
2P1
2VQ
2~H
30V
3V.
4.4
406
408
409
40D
40E
44B
53G
5GY
5VS
67Z
6NX
78A
7WY
7X7
8AO
8FI
8FJ
8FL
8FW
8TC
8UJ
8VB
95-
95.
95~
96X
AAAVM
AABHQ
AACDK
AAHNG
AAIAL
AAJBT
AAJKR
AANXM
AANZL
AARHV
AARTL
AASML
AATNV
AATVU
AAUYE
AAWCG
AAWTL
AAYIU
AAYQN
AAYTO
AAYZH
ABAKF
ABBBX
ABBXA
ABDZT
ABECU
ABFTV
ABHLI
ABHQN
ABJNI
ABJOX
ABKCH
ABKTR
ABMNI
ABMQK
ABNWP
ABPLI
ABQBU
ABQSL
ABSXP
ABTEG
ABTKH
ABTMW
ABULA
ABUWG
ABWNU
ABXPI
ACAOD
ACDTI
ACGFS
ACHSB
ACHXU
ACKNC
ACMDZ
ACMLO
ACOKC
ACOMO
ACPIV
ACSNA
ACZOJ
ADBBV
ADHHG
ADHIR
ADINQ
ADKNI
ADKPE
ADRFC
ADTPH
ADURQ
ADYFF
ADZKW
AEBTG
AEFQL
AEGAL
AEGNC
AEJHL
AEJRE
AEKMD
AEMSY
AEOHA
AEPYU
AESKC
AETLH
AEVLU
AEXYK
AFBBN
AFGCZ
AFKRA
AFLOW
AFQWF
AFWTZ
AFZKB
AGAYW
AGDGC
AGJBK
AGMZJ
AGQEE
AGQMX
AGRTI
AGWIL
AGWZB
AGYKE
AHAVH
AHBYD
AHKAY
AHMBA
AHQJS
AHSBF
AHYZX
AIAKS
AIGIU
AIIXL
AILAN
AITGF
AJBLW
AJRNO
AJZVZ
AKMHD
AKVCP
ALIPV
ALMA_UNASSIGNED_HOLDINGS
ALWAN
AMKLP
AMXSW
AMYLF
AMYQR
AOCGG
AQUVI
ARMRJ
ASPBG
AVWKF
AXYYD
AZFZN
B-.
BA0
BAPOH
BDATZ
BENPR
BEZIV
BGNMA
BPHCQ
BSONS
BVXVI
CAG
CCPQU
COF
CS3
CSCUP
DDRTE
DL5
DNIVK
DPUIP
DWQXO
EBLON
EBS
EBU
EHB
EHE
EIOEI
EJD
ESBYG
F5P
FEDTE
FERAY
FFXSO
FIGPU
FINBP
FNLPD
FRNLG
FRRFC
FSGXE
FWDCC
FYUFA
GGCAI
GGRSB
GJIRD
GNWQR
GQ6
GQ7
GQ8
GROUPED_ABI_INFORM_COMPLETE
GROUPED_ABI_INFORM_RESEARCH
GXS
H13
HF~
HG5
HG6
HMCUK
HMJXF
HQYDN
HRMNR
HVGLF
HZ~
I09
IHE
IJ-
IKXTQ
IWAJR
IXC
IXD
IXE
IZIGR
IZQ
I~X
I~Z
J-C
J0Z
JBSCW
JCJTX
JZLTJ
K1G
K60
K6~
KDC
KOV
LAK
LLZTM
M0C
M0T
M4Y
MA-
MK0
N2Q
NPVJJ
NQJWS
NU0
O9-
O93
O9J
OAM
OVD
P9L
PF0
PQBIZ
PQBZA
PQQKQ
PROAC
PT4
Q2X
QOR
QOS
QWB
R89
R9I
RNI
ROL
RPX
RSV
RZC
RZE
S16
S1Z
S27
S3B
SAP
SDH
SHX
SISQX
SJYHP
SMD
SNE
SNPRN
SNX
SOHCF
SOJ
SPISZ
SRMVM
SSLCW
SSXJD
STPWE
SZ9
SZN
T13
TEORI
TH9
TSG
TSK
TSV
TUC
TUS
U2A
U9L
UG4
UKHRP
UOJIU
UTJUX
UZXMN
VC2
VFIZW
W23
W48
WK8
YLTOR
Z45
ZL0
ZMTXR
ZOVNA
~8M
~A9
AAPKM
AAYXX
ABBRH
ABDBE
ABFSG
ABRTQ
ACSTC
ADHKG
AEZWR
AFDZB
AFFHD
AFHIU
AFOHR
AGQPQ
AHPBZ
AHWEU
AIXLP
ATHPR
AYFIA
CITATION
PHGZM
PHGZT
PJZUB
PPXIY
7XB
8FK
K9.
L.-
PKEHL
PQEST
PQUKI
Q9U
ID FETCH-LOGICAL-c319t-483627d35e71e8dd86e186aa06b530912d08ee84aece3d199f53d78d58f3446f3
IEDL.DBID BENPR
ISICitedReferencesCount 3
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000559146800001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 1387-3741
IngestDate Wed Nov 05 02:12:49 EST 2025
Sat Nov 29 03:39:09 EST 2025
Tue Nov 18 20:48:37 EST 2025
Fri Feb 21 02:42:43 EST 2025
IsPeerReviewed false
IsScholarly true
Issue 4
Keywords Mixed effect models
Intensive longitudinal data
Latent class classification
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c319t-483627d35e71e8dd86e186aa06b530912d08ee84aece3d199f53d78d58f3446f3
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ORCID 0000-0003-2463-1272
PQID 2608622134
PQPubID 26116
PageCount 15
ParticipantIDs proquest_journals_2608622134
crossref_primary_10_1007_s10742_020_00217_5
crossref_citationtrail_10_1007_s10742_020_00217_5
springer_journals_10_1007_s10742_020_00217_5
PublicationCentury 2000
PublicationDate 20201200
2020-12-00
20201201
PublicationDateYYYYMMDD 2020-12-01
PublicationDate_xml – month: 12
  year: 2020
  text: 20201200
PublicationDecade 2020
PublicationPlace New York
PublicationPlace_xml – name: New York
– name: Dordrecht
PublicationSubtitle An International Journal Devoted to Methods for the Study of the Utilization, Quality, Cost and Outcomes of Health Care
PublicationTitle Health services and outcomes research methodology
PublicationTitleAbbrev Health Serv Outcomes Res Method
PublicationYear 2020
Publisher Springer US
Springer Nature B.V
Publisher_xml – name: Springer US
– name: Springer Nature B.V
References Langeheine, van de Pol (CR11) 2000; 5
Shiffman, Stone, Hufford (CR21) 2008; 4
Jackson, Albert, Zhang (CR10) 2015; 9
Piasecki, Hedeker, Dierker, Mermelstein (CR17) 2016; 30
Lin, Mermelstein, Hedeker (CR14) 2018; 18
Hedeker, Mermelstein, Demirtas (CR9) 2008; 64
Gales, Young (CR6) 2008; 1
Crayen, Eid, Lischetzke, Courvoisier, Vermunt (CR4) 2012; 74
Stone, Shiffman (CR24) 1994; 16
Choo, Tong, Zhang (CR3) 2004; 2
Cappe (CR2) 2011; 20
MacDonald, Zucchini (CR16) 1997
Rocke, Li, Smith (CR19) 2009; 24
Seltman, Gatsonis, Kass, Carriquiry, Gelman, Higdon, Pauler, Verdinelli (CR20) 2002
Altman (CR1) 2007; 102
Liu, Li, Li, Song, Rehg (CR15) 2015; 28
Goldstein, Leckie, Charlton, Tilling, Browne (CR8) 2018; 27
Leckie, French, Charlton, Browne (CR12) 2014; 39
CR23
Vehtari, Gelman, Gabry (CR25) 2017; 27
de Haan-Rietdijk, Kuppens, Bergeman, Sheeber, Allen, Hamaker (CR5) 2017; 52
Shirley, Small, Lynch, Maisto, Oslin (CR22) 2010; 4
Ghahramani (CR7) 2001; 15
Rast, Hofer, Sparks (CR18) 2012; 47
Lin, Mermelstein, Hedeker (CR13) 2018; 37
IL MacDonald (217_CR16) 1997
S de Haan-Rietdijk (217_CR5) 2017; 52
R Langeheine (217_CR11) 2000; 5
X Lin (217_CR14) 2018; 18
G Leckie (217_CR12) 2014; 39
TM Piasecki (217_CR17) 2016; 30
JC Jackson (217_CR10) 2015; 9
HJ Seltman (217_CR20) 2002
C Rocke (217_CR19) 2009; 24
C Crayen (217_CR4) 2012; 74
P Rast (217_CR18) 2012; 47
Y Liu (217_CR15) 2015; 28
KH Choo (217_CR3) 2004; 2
D Hedeker (217_CR9) 2008; 64
S Shiffman (217_CR21) 2008; 4
H Goldstein (217_CR8) 2018; 27
O Cappe (217_CR2) 2011; 20
KE Shirley (217_CR22) 2010; 4
Z Ghahramani (217_CR7) 2001; 15
RM Altman (217_CR1) 2007; 102
A Vehtari (217_CR25) 2017; 27
M Gales (217_CR6) 2008; 1
217_CR23
AA Stone (217_CR24) 1994; 16
X Lin (217_CR13) 2018; 37
References_xml – volume: 27
  start-page: 1413
  issue: 5
  year: 2017
  end-page: 1432
  ident: CR25
  article-title: Practical bayesian model evaluation using leave-one-out cross-validation and waic
  publication-title: Stat. Comput.
  doi: 10.1007/s11222-016-9696-4
– volume: 102
  start-page: 201
  issue: 477
  year: 2007
  end-page: 210
  ident: CR1
  article-title: Mixed hidden Markov models: an extension of the hidden Markov model to the longitudinal data setting
  publication-title: J. Am. Stat. Assoc.
  doi: 10.1198/016214506000001086
– volume: 27
  start-page: 3478
  issue: 11
  year: 2018
  end-page: 3491
  ident: CR8
  article-title: Multilevel growth curve models that incorporate a random coefficient model for the level 1 variance function
  publication-title: Stat. Methods Med. Res.
  doi: 10.1177/0962280217706728
– volume: 37
  start-page: 2108
  issue: 13
  year: 2018
  end-page: 2119
  ident: CR13
  article-title: A 3-level bayesian mixed effects location scale model with an application to ecological momentary assessment data
  publication-title: Stat. Med.
  doi: 10.1002/sim.7627
– volume: 64
  start-page: 627
  issue: 2
  year: 2008
  end-page: 634
  ident: CR9
  article-title: An application of a mixed-effects location scale model for analysis of ecological momentary assessment (EMA) data
  publication-title: Biometrics
  doi: 10.1111/j.1541-0420.2007.00924.x
– volume: 39
  start-page: 307
  issue: 5
  year: 2014
  end-page: 332
  ident: CR12
  article-title: Modeling heterogeneous variance-covariance components in two-level models
  publication-title: J. Educ. Behav. Stat.
  doi: 10.3102/1076998614546494
– volume: 28
  start-page: 3599
  year: 2015
  end-page: 3607
  ident: CR15
  article-title: Efficient learning of continuous-time hidden Markov models for disease progression
  publication-title: Adv. Neural Inf. Process. Syst.
– volume: 18
  start-page: 227
  issue: 4
  year: 2018
  end-page: 243
  ident: CR14
  article-title: A shared parameter location scale mixed effect model for ema data subject to informative missing
  publication-title: Health Serv. Outcomes Res. Methodol.
  doi: 10.1007/s10742-018-0184-5
– volume: 24
  start-page: 863
  issue: 4
  year: 2009
  end-page: 878
  ident: CR19
  article-title: Intraindividual variability in positive and negative affect over 45 days: do older adults fluctuate less than young adults?
  publication-title: Psychol. Aging
  doi: 10.1037/a0016276
– volume: 4
  start-page: 1
  year: 2008
  end-page: 32
  ident: CR21
  article-title: Ecological momentary assessment
  publication-title: Ann. Rev. Clin. Psychol.
  doi: 10.1146/annurev.clinpsy.3.022806.091415
– volume: 4
  start-page: 366
  issue: 1
  year: 2010
  end-page: 395
  ident: CR22
  article-title: Hidden Markov models for alcoholism treatment trial data
  publication-title: Ann. Appl. Stat.
  doi: 10.1214/09-AOAS282
– ident: CR23
– volume: 74
  start-page: 366
  issue: 4
  year: 2012
  end-page: 376
  ident: CR4
  article-title: Exploring dynamics in mood rgulation—mixture latent markov modeling of ambulatory assessment data
  publication-title: Psychosom. Med.
  doi: 10.1097/PSY.0b013e31825474cb
– volume: 30
  start-page: 484
  issue: 4
  year: 2016
  end-page: 493
  ident: CR17
  article-title: Progression of nicotine dependence, mood level, and mood variability in adolescent smokers
  publication-title: Psychol. Addict. Behav.
  doi: 10.1037/adb0000165
– volume: 47
  start-page: 177
  issue: 2
  year: 2012
  end-page: 200
  ident: CR18
  article-title: Modeling individual differences in within-person variation of negative and positive affect in a mixed effects location scale model using BUGS/JAGS
  publication-title: Multivar. Behav. Res.
  doi: 10.1080/00273171.2012.658328
– volume: 20
  start-page: 728
  issue: 3
  year: 2011
  end-page: 749
  ident: CR2
  article-title: Online EM algorithm for hidden Markov models
  publication-title: J. Comput. Gr. Stat.
  doi: 10.1198/jcgs.2011.09109
– year: 1997
  ident: CR16
  publication-title: Hidden Markov Models and Other Models for Discrete-Value Time Series
– volume: 2
  start-page: 84
  issue: 2
  year: 2004
  end-page: 96
  ident: CR3
  article-title: Recent applications of hidden Markov models in computational biology
  publication-title: Genom. Proteom. Bioinform.
  doi: 10.1016/S1672-0229(04)02014-5
– volume: 5
  start-page: 33
  issue: 1
  year: 2000
  end-page: 54
  ident: CR11
  article-title: Fitting higher order Markov chains
  publication-title: Methods Psychol. Res.
– volume: 15
  start-page: 9
  issue: 1
  year: 2001
  end-page: 42
  ident: CR7
  article-title: An introduction to hidden Markov models and bayesian networks
  publication-title: Int. J. Pattern Recogn. Artif. Intell.
  doi: 10.1142/S0218001401000836
– volume: 9
  start-page: 849
  issue: 2
  year: 2015
  end-page: 865
  ident: CR10
  article-title: A two-state mixed hidden Markov model for risky teenage driving behavior
  publication-title: Ann. Appl. Stat.
  doi: 10.1214/14-AOAS765
– volume: 16
  start-page: 199
  issue: 3
  year: 1994
  end-page: 202
  ident: CR24
  article-title: Ecological momentary assessment (EMA) in behavioral medicine
  publication-title: Ann. Behav. Med.
  doi: 10.1093/abm/16.3.199
– start-page: 397
  year: 2002
  end-page: 405
  ident: CR20
  article-title: Hidden Markov models for analysis of biological rhythm data
  publication-title: Case Studies in Bayesian Statistics
– volume: 1
  start-page: 195
  issue: 3
  year: 2008
  end-page: 304
  ident: CR6
  article-title: The application of hidden Markov models in speech recognition
  publication-title: Found. Trends Signal Process.
  doi: 10.1561/2000000004
– volume: 52
  start-page: 747
  issue: 6
  year: 2017
  end-page: 767
  ident: CR5
  article-title: On the use of mixed Markov models for intensive longitudinal data
  publication-title: Multivar. Behav. Res.
  doi: 10.1080/00273171.2017.1370364
– volume: 9
  start-page: 849
  issue: 2
  year: 2015
  ident: 217_CR10
  publication-title: Ann. Appl. Stat.
  doi: 10.1214/14-AOAS765
– volume: 15
  start-page: 9
  issue: 1
  year: 2001
  ident: 217_CR7
  publication-title: Int. J. Pattern Recogn. Artif. Intell.
  doi: 10.1142/S0218001401000836
– volume: 27
  start-page: 3478
  issue: 11
  year: 2018
  ident: 217_CR8
  publication-title: Stat. Methods Med. Res.
  doi: 10.1177/0962280217706728
– volume: 16
  start-page: 199
  issue: 3
  year: 1994
  ident: 217_CR24
  publication-title: Ann. Behav. Med.
  doi: 10.1093/abm/16.3.199
– volume: 30
  start-page: 484
  issue: 4
  year: 2016
  ident: 217_CR17
  publication-title: Psychol. Addict. Behav.
  doi: 10.1037/adb0000165
– volume: 102
  start-page: 201
  issue: 477
  year: 2007
  ident: 217_CR1
  publication-title: J. Am. Stat. Assoc.
  doi: 10.1198/016214506000001086
– volume: 37
  start-page: 2108
  issue: 13
  year: 2018
  ident: 217_CR13
  publication-title: Stat. Med.
  doi: 10.1002/sim.7627
– volume: 1
  start-page: 195
  issue: 3
  year: 2008
  ident: 217_CR6
  publication-title: Found. Trends Signal Process.
  doi: 10.1561/2000000004
– start-page: 397
  volume-title: Case Studies in Bayesian Statistics
  year: 2002
  ident: 217_CR20
– volume: 28
  start-page: 3599
  year: 2015
  ident: 217_CR15
  publication-title: Adv. Neural Inf. Process. Syst.
– ident: 217_CR23
– volume: 4
  start-page: 366
  issue: 1
  year: 2010
  ident: 217_CR22
  publication-title: Ann. Appl. Stat.
  doi: 10.1214/09-AOAS282
– volume-title: Hidden Markov Models and Other Models for Discrete-Value Time Series
  year: 1997
  ident: 217_CR16
– volume: 52
  start-page: 747
  issue: 6
  year: 2017
  ident: 217_CR5
  publication-title: Multivar. Behav. Res.
  doi: 10.1080/00273171.2017.1370364
– volume: 5
  start-page: 33
  issue: 1
  year: 2000
  ident: 217_CR11
  publication-title: Methods Psychol. Res.
– volume: 4
  start-page: 1
  year: 2008
  ident: 217_CR21
  publication-title: Ann. Rev. Clin. Psychol.
  doi: 10.1146/annurev.clinpsy.3.022806.091415
– volume: 47
  start-page: 177
  issue: 2
  year: 2012
  ident: 217_CR18
  publication-title: Multivar. Behav. Res.
  doi: 10.1080/00273171.2012.658328
– volume: 39
  start-page: 307
  issue: 5
  year: 2014
  ident: 217_CR12
  publication-title: J. Educ. Behav. Stat.
  doi: 10.3102/1076998614546494
– volume: 18
  start-page: 227
  issue: 4
  year: 2018
  ident: 217_CR14
  publication-title: Health Serv. Outcomes Res. Methodol.
  doi: 10.1007/s10742-018-0184-5
– volume: 74
  start-page: 366
  issue: 4
  year: 2012
  ident: 217_CR4
  publication-title: Psychosom. Med.
  doi: 10.1097/PSY.0b013e31825474cb
– volume: 20
  start-page: 728
  issue: 3
  year: 2011
  ident: 217_CR2
  publication-title: J. Comput. Gr. Stat.
  doi: 10.1198/jcgs.2011.09109
– volume: 24
  start-page: 863
  issue: 4
  year: 2009
  ident: 217_CR19
  publication-title: Psychol. Aging
  doi: 10.1037/a0016276
– volume: 2
  start-page: 84
  issue: 2
  year: 2004
  ident: 217_CR3
  publication-title: Genom. Proteom. Bioinform.
  doi: 10.1016/S1672-0229(04)02014-5
– volume: 64
  start-page: 627
  issue: 2
  year: 2008
  ident: 217_CR9
  publication-title: Biometrics
  doi: 10.1111/j.1541-0420.2007.00924.x
– volume: 27
  start-page: 1413
  issue: 5
  year: 2017
  ident: 217_CR25
  publication-title: Stat. Comput.
  doi: 10.1007/s11222-016-9696-4
SSID ssj0022068
Score 2.2027688
Snippet Hidden Markov models (HMM) presents an attractive analytical framework for capturing the state-switching process for auto-correlated data. These models have...
SourceID proquest
crossref
springer
SourceType Aggregation Database
Enrichment Source
Index Database
Publisher
StartPage 222
SubjectTerms Behavior
Data compression
Economics
Health Administration
Health services
Latent class analysis
Longitudinal studies
Markov analysis
Medicine
Medicine & Public Health
Methodology of the Social Sciences
Probability
Public Health
Research methodology
Statistics
Teenagers
SummonAdditionalLinks – databaseName: SpringerLINK Contemporary 1997-Present
  dbid: RSV
  link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3dS8MwED90ig7Ej6k4nZIH3zSwpk2TPIo4fNkQv9hbaZsUBelk3YZ_vpe03VRU0OcmoeRyufvl7n4HcBokqUTcENI04YwGCDpoEquYCrR1iYmZp1Ximk2IwUAOh-qmKgor6mz3OiTpbuoPxW4I46iFO86RpnwZVtDcSauOt3ePc5jFumUBnO_UJ_CqUpnv1_hsjhY-5pewqLM2va3__ec2bFbeJbkoj8MOLJm8Bet18XHRgrV-FUtvwUb5YkfKQqQWNK3fWdI278Kw__xmNLGWzkqOFChKQ54s30hObH3PaEZcEx2CTi9BJ5LEFbsJGWXkuc6LxwVsP6Sptr23iM1G3YOH3tX95TWtmjDQFLVzYh8bQya0z43wjNRahsaTYRx3w4T76Gww3ZXGyCA2qfG1p1TGfS2k5jLzEWpm_j408lFuDoDYkKfKUiG0ZkEiMkRaqWGKa4FThVJt8GpZRGnFUG4bZbxEC25lu7cR7m3k9jbibTibz3kt-Tl-Hd2pRRxVulpEiOgQ1llmuzac1yJdfP55tcO_DT-CJrOnwuXCdKAxGU_NMaymM5Tt-MSd4Xex9-gt
  priority: 102
  providerName: Springer Nature
Title Mixed location scale hidden Markov model for the analysis of intensive longitudinal data
URI https://link.springer.com/article/10.1007/s10742-020-00217-5
https://www.proquest.com/docview/2608622134
Volume 20
WOSCitedRecordID wos000559146800001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVAVX
  databaseName: SpringerLINK Contemporary 1997-Present
  customDbUrl:
  eissn: 1572-9400
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0022068
  issn: 1387-3741
  databaseCode: RSV
  dateStart: 20000301
  isFulltext: true
  titleUrlDefault: https://link.springer.com/search?facet-content-type=%22Journal%22
  providerName: Springer Nature
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1LSwMxEB60FfHiW6wvcvCmwe4zyUlUWry0FJ_1tOwmWSxIq7aKP9-ZNGtR0IuXwLKbsOyX7HyTzMwHcBgXWqLfkHJdJCGP0engRa5yLtDWFTYPA6MKJzYhul3Z76ue33Ab-7DK6p_oftRmpGmP_AR5N5Jvqj92-vzCSTWKTle9hMY81KlSWVyD-nmr27v6crnC5jQZLnJLKQ582oxPnkO3kJP75Ig5T76bphnf_HFE6ixPe-W_77wKy55zsrPpJFmDOTtch8WOP1XfgH5n8GENI7NGMLEx4mbZIxUXGTJK5hm9M6eYw5DhMmSMLPelTNioZIMqCB4HIPGjN0NCW4xCTzfhtt26ubjkXnGBa1yKE9pZTENhosSKwEpjZGoDmeZ5My2SCJlFaJrSWhnnVtvIBEqVSWSENIksI_Qry2gLasPR0G4Do_NNVWohjAnjQpToVmkbqsQI7CqUakBQfexM-3LkpIrxlM0KKRNAGQKUOYCypAFHX32ep8U4_nx6r0Il8wtznM0gacBxhevs9u-j7fw92i4shTSVXKDLHtQmr292Hxb0-2Qwfj2AeXH_QG1fHPgpiled5oVrb7C9ur77BPtm63U
linkProvider ProQuest
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1LTxsxEB5BqIAL9IUITx_aE7Wa9T5sH1BVFRAoD3EIUm7bXdsrIqEkJOH1p_iNzDi7RFQqNw6cdz3Srj975rNn5gP4FuVGIW9IuMljwSMkHTzPdMYl-rrcZSKwOvdiE7LTUb2ePl-Ax6oWhtIqqz3Rb9R2aOiM_CfG3Rh8U_-xX6NrTqpRdLtaSWjMYNF0D3dI2SaHZ0c4v9-FODnu_jnlpaoANwi3KZ2eJULaMHYycMpalbhAJVnWSPI4RO8pbEM5p6LMGRfaQOsiDq1UNlZFiNypCNHuIixRXz1KIWw3us8ETzRmpXehX7hRUBbplKV6SEI5kTVPA3j80hHOo9t_LmS9nztZf29_6COslRE1-z1bAp9gwQ0-w3K7zBn4Ar12_95ZRk6bQMgmiErHLql1yoBRqdLwlnk9IIbxO8N4mGVloxY2LFi_SvFHAyTtdGNJRoxRYu1XuHiT79qA2mA4cJvA6PZWF0ZKa0WUywJJo3FCx1biUKl1HYJqclNTNlsnzY-rdN4mmgCRIiBSD4g0rsPB85jRrNXIq2_vVChIy21nks4hUIcfFY7mj_9vbet1a_uwctptt9LWWae5DauCYOxTenagNh3fuF34YG6n_cl4zy8IBn_fGl9Pkc9BMg
linkToPdf http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V3BTtwwEB1RilAvbYFW3QKtD3ACi40Tx_YBVQi6KoJdcQBpbyGxHbFStQvsAu2v8XXMeB1WIJUbh54Tj5T42TPPnpkHsJFVViNvyLmtpOAZkg5elabkCn1d5UuROFMFsQnV6-l-35zMwX1TC0Nplc2eGDZqN7J0Rr6DcTcG39R_bKeOaREnB50fl1ecFKToprWR05hC5Mj_vUP6Nt49PMC53hSi8_N0_xePCgPcIvQmdJKWC-VS6VXitXM694nOy7KdVzJFTypcW3uvs9Jbn7rEmFqmTmkndZ0ij6pTtPsG3qpMCiJ-3fbpI9kT7WkZXhoWcZbEgp1YtoeElBNxC5SAy6dOcRbpPrucDT6v8-F__lsf4X2MtNnedGkswZwfLsNiN-YSrEC_O_jjHSNnTuBkY0SrZxfUUmXIqIRpdMuCThDDuJ5hnMzK2MCFjWo2aFL_0QBJPt04khdjlHD7Cc5e5bs-w_xwNPRfgNGtrqmtUs6JrFI1kknrhZFO4VBlTAuSZqILG5uwkxbI72LWPprAUSA4igCOQrZg63HM5bQFyYtvrzWIKOJ2NC5mcGjBdoOp2eN_W_v6srXvsIiwKo4Pe0er8E4QokOmzxrMT65v_Dos2NvJYHz9LawNBuevDa8HeMpJ-A
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Mixed+location+scale+hidden+Markov+model+for+the+analysis+of+intensive+longitudinal+data&rft.jtitle=Health+services+and+outcomes+research+methodology&rft.au=Lin%2C+Xiaolei&rft.au=Mermelstein%2C+Robin&rft.au=Hedeker%2C+Donald&rft.date=2020-12-01&rft.pub=Springer+Nature+B.V&rft.issn=1387-3741&rft.eissn=1572-9400&rft.volume=20&rft.issue=4&rft.spage=222&rft.epage=236&rft_id=info:doi/10.1007%2Fs10742-020-00217-5&rft.externalDBID=HAS_PDF_LINK
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1387-3741&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1387-3741&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1387-3741&client=summon