Search results for "Time-varying covariate"

showing 3 items of 3 documents

Effects of Visually Induced Motion Sickness on Emergency Braking Reaction Times in a Driving Simulator

2019

Objective: The study explores associations of visually induced motion sickness (VIMS) with emergency braking reaction times (RTs) in driving simulator studies. It examines the effects over the progression of multiple simulated drives. Background: Driving simulator usage has many advantages for RT studies; however, if it induces VIMS, the observed driving behavior might deviate from real-world driving, potentially masking or skewing results. Possible effects of VIMS on RT have long been entertained, but the progression of VIMS across simulated drives has so far not been sufficiently considered. Method: Twenty-eight adults completed six drives on 2 days in a fixed-base driving simulator. At f…

AdultMaleTime-varying covariateAutomobile DrivingMotion SicknessComputer scienceHuman Factors and ErgonomicsYoung AdultBehavioral Neuroscience0502 economics and businessReaction TimemedicineHumansDriving simulationComputer Simulation0501 psychology and cognitive sciences050107 human factorsApplied PsychologySimulation050210 logistics & transportation05 social sciencesDriving simulatormedicine.diseaseMotion sicknessSimulator sicknessFemaleEmergencies
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Comment on ‘Generating survival times to simulate Cox proportional hazards models with time-varying covariates’

2013

Statistics and ProbabilityTime-varying covariateta112EpidemiologyProportional hazards modelStatisticsSurvival analysisMathematicsStatistics in Medicine
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Efficient design and modeling strategies for follow-up studies with time-varying covariates

2015

Epidemiological studies can often be designed in several ways, some of which may be more optimal than others. Possible designs may differ in the required resources or the ability to provide reliable answers to the questions under study. In addition, once the data are collected, the selected modeling approach may affect how efficiently the data are utilized. The purpose of this dissertation is to investigate efficient designs and analysis meth ods in follow-up studies with longitudinal measurements. A key question is how to select optimally a subcohort for a new longitudinal covariate measurement if we cannot afford to measure the entire cohort. Another key question we consider is how to determine …

kuolleisuustime-varying covariatesdata collectionkustannustehokkuusanalyysimenetelmätennusteetfollow-up studypitkittäistutkimusoptimaalisuusrisk predictiondataaikariippuvat kovariaatitSeurantatutkimustutkimusmenetelmätsydän- ja verisuonitauditcardiovascular disease mortalitylongitudinal measurementssimulointioptimal designepidemiologiakohorttitutkimustutkimusaineistoterveysriskit
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