Search results for "support model"

showing 4 items of 4 documents

Multilevel Latent Profile Analysis With Covariates : Identifying Job Characteristics Profiles in Hierarchical Data as an Example

2018

Latent profile analysis (LPA) is a person-centered method commonly used in organizational research to identify homogeneous subpopulations of employees within a heterogeneous population. However, in the case of nested data structures, such as employees nested in work departments, multilevel techniques are needed. Multilevel LPA (MLPA) enables adequate modeling of subpopulations in hierarchical data sets. MLPA enables investigation of variability in the proportions of Level 1 profiles across Level 2 units, and of Level 2 latent classes based on the proportions of Level 1 latent profiles and Level 1 ratings, and the extent to which covariates drawn from the different hierarchical levels of the…

ominaisuudetmultilevel latent profile analysishierarchical structurejob demand-control-support modeltyöntekijätanalyysiclustered datatyöprofiilit (tieto)
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Sosiaalisen elämän kehykset : kampus-ohjelman opiskelijoiden sosiaalinen asema tuetussa aikuisopiskelussa ja vapaa-ajalla

2012

support modelEtnometodologiasocial exclusionKampus-ohjelmamarginalizationethnomethodologyethnographysocial relationshipssosiaaliset suhteetinclusionmedicalisationsosiaaliset verkostotstigmaerityisopetussocial capitalfriendshipsfunctional assessmentothernesskehitysvammaisetecological analysisinkluusioaikuisopiskelu
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Multilevel Latent Profile Analysis With Covariates : Identifying Job Characteristics Profiles in Hierarchical Data as an Example

2018

Latent profile analysis (LPA) is a person-centered method commonly used in organizational research to identify homogeneous subpopulations of employees within a heterogeneous population. However, in the case of nested data structures, such as employees nested in work departments, multilevel techniques are needed. Multilevel LPA (MLPA) enables adequate modeling of subpopulations in hierarchical data sets. MLPA enables investigation of variability in the proportions of Level 1 profiles across Level 2 units, and of Level 2 latent classes based on the proportions of Level 1 latent profiles and Level 1 ratings, and the extent to which covariates drawn from the different hierarchical levels of th…

multilevel latent profile analysisComputer scienceStrategy and ManagementGeneral Decision SciencestyöHierarchical database model0504 sociologyManagement of Technology and Innovation0502 economics and businessStatisticsCovariatetyöntekijätjob demand-control-support modelClustered dataclustered datata515Analysis of covarianceta11205 social sciences050401 social sciences methodsMixture modelprofiilit (tieto)Heterogeneous populationominaisuudetHomogeneoushierarchical structureanalyysiJob demand control support model050203 business & managementOrganizational Research Methods
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Latvijas alus iespēju analīze eksportam uz Latīņameriku

2022

Maģistra darba tēma ir “Analīze par Latvijas alus eksporta iespējām Latīņamerikā”. Darba autore ir Jarlotte Camila Quintero Martinez un darba vadītājs - Prof., Erika Sumilo. Maģistra darba mērķis ir noteikt, kurš modelis tiks izmantots starptautiskā tirgus atlasei, un veikt Latīņamerikas tirgus izpēti, lai noskaidrotu, kura šī reģiona valsts būtu piemērotākā Latvijas alus eksportam. Lai sasniegtu maģistra darba mērķi, tiek veikta Latīņamerikas valstu izpēte, īstenota teorētiskā materiāla analīze par starptautisko tirgus atlases modeļu raksturojumu, kā arī riska pārvaldības un eksporta barjerām, tā rezultātā nosakot valsti ar labāko vidi Latvijas alus eksportam. Maģistra darbs sastāv no piec…

VadībzinātneDecision Support ModelRisk ManagementInternational Market Selection ModelsExportBeer industry
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