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On the use of multiple imputation in handling missing values in longitudinal studiesChan, Pui-shan, 陳佩珊 January 2004 (has links)
published_or_final_version / Medical Sciences / Master / Master of Medical Sciences
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Longitudinal analysis of the effect of climatic factors on the wood anatomy of two eucalypt clones.Ayele, Dawit Getnet. 04 February 2014 (has links)
Eucalypt trees are one of tree species used for the manufacturing of papers in
South Africa. The manufacturing of paper consists of cooking the wood with chemicals until
obtaining a pulp. The wood is made of different cells. The shape and structure of these cells, called
wood anatomical characteristics are important for the quality of paper. In addition, the anatomical
characteristics of wood are influenced by environmental factors like climatic factors, soil
compositions etc…. In this study we investigated the effects of the climatic factors (temperature,
rainfall, solar radiation, relative humidity, and wind speed) on wood anatomical characteristics of
two Eucalyptus clones, a GC (Eucalyptus grandis × camuldulensis) and a GU (Eucalyptus grandis ×
urophylla). Nine trees per clone have been selected.
Two sets of data have been collected for this study. The first set of data was eleven anatomical
characteristics of the wood formed daily over a period of five years. The second set of data was the
daily measurement of temperature, rainfall, solar radiation, relative humidity and wind speed in the
experimental area.
Wood is made of two kinds of cell, the fibres and the vessels. The fibres are used for the strength and
support of the tree and the vessels for the nutrition. Eleven characteristics related to those cells have
been measured (diameter, wall thickness, frequency). These characteristics are highly correlated. To
reduce the number of response variables, the principal component analysis was used and the first four
principal components accounts for about 95% of the total variation. Based on the weights associated
with each component the first four principal components were labelled as vessel dimension (VD),
fibre dimension (FD), fibre wall (FW) and vessel frequency (VF).
The longitudinal linear mixed model with age, season, temperature, rainfall, solar radiation, relative
humidity and wind speed as the fixed effects factors and tree as random effect factor was fitted to the
data. From time series modelling result, lagged order of climatic variables were identified and these
lagged climatic variables were included in the model. To account for the physical characteristic of
the trees we included the effect of diameter at breast height, stem radius, daily radial increment, and
the suppression or dominance of the tree in the model. It was found that wood anatomical
characteristics of the two clones were more affected by climatic variables when the tree was on
juvenile stage as compared to mature stage. / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2010.
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Modelling longitudinal counts data with application to recurrent epileptic seizure events.Ngulube, Phathisani. January 2010 (has links)
The objectives of this thesis is to explore different approaches of modelling clustered correlated data in the form of repeated or longitudinal counts data leading to a replicated Poisson process. The specific application is from repeated epileptic seizure time to events data. Two main classes of models will be considered in this thesis. These are the marginal and subject or cluster specific effects models. Under the marginal class of models the generalized estimating equations approach due to Liang and Zeger (1986) is first considered. These models are concerned with population averaged effects as opposed to subject-specific effects which include random subject-specific effects such that multiple or repeated outcomes within a subject or cluster are assumed to be independent conditional on the subject−specific effects.
Finally we consider a distinct class of marginal models which include three common variants namely the approach due to Anderson and Gill (1982), Wei et al (1989) and Prentice et al. (1981) / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2010.
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Evaluation of information in longitudinal dataPetzold, Max. January 2003 (has links)
Thesis (doctoral)--Göteborg University, 2003. / Includes bibliographical references.
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Stochastic models for MRI lesion count sequences from patients with relapsing remitting multiple sclerosisLi, Xiaobai, January 2006 (has links)
Thesis (Ph. D.)--Ohio State University, 2006. / Title from first page of PDF file. Includes bibliographical references (p. 122-125).
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Bayesian analysis of longitudinal models /Husain, Syeda Tasmine, January 2003 (has links)
Thesis (M.A.S.)--Memorial University of Newfoundland, 2003. / Bibliography: leaves 68-70. Also available online.
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A continuous-time Markov chain approach for trinomial-outcome longitudinal data : an extension for multiple covariates.Mhoon, Kendra Brown. Moyé, Lemuel A., Mullen, Patricia D., Vernon, Sally W., January 2008 (has links)
Thesis (Ph. D.)--University of Texas Health Science Center at Houston, School of Public Health, 2008. / Source: Dissertation Abstracts International, Volume: 69-02, Section: B, page: 1086. Adviser: Wenyaw Chan. Includes bibliographical references.
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The measurement of change in well-being in a longitudinal study of pre- and post-retireesBeaudet, Marie P. 01 January 1985 (has links)
The primary focus of this dissertation is an empirical investigation of three approaches to the measurement of longitudinal change. For the present study, difference scores, residual change scores, and percentage gain scores are compared to determine if their use results in similar findings when the relationships between three resource areas (health, social, and financial) and subjective well-being are analyzed. The propositions which are tested were derived from current aging theories. Meta-analysis procedures were employed to synthesize past research findings in gerontology. The data which were analyzed are those of the Longitudinal Retirement History Study (LRHS), a research project sponsored by the Social Security Administration. The sample consists of 8922 continuers who participated in the 1969, 1971, and 1973 waves of data collection. Findings from the meta-analysis suggest that the correlation coefficients calculated from the LRHS data on the relationship between subjecive well-being and the areas of health resources and social resources are similar to those of other aging studies. The relationship between measures of financial resources and subjective well-being is stronger for the LRHS respondents than that reported in other aging studies. The results on the analysis of longitudinal change indicate that change in health resources and in financial resources are significant predictors of subjective well-being at a later-point-in-time and of change in subjective well-being. For the present study, change in social resources contributes little to the regression equations. The three selected approaches to the measurement of change rank individuals similarly on the construct of change. However, the use of difference scores, residual change scores, and percentage gain scores does not always result in similar findings when multivariate procedures are used. Residual change scores appear to possess a number of advantages. They tend, however, to be strongly related to the time 2 scores from which they are derived, a phenomenon not emphasized in the measurement of change literature. Improving the reliability of measures, allowing adequate time for change to occur, and using sample sizes which are large are suggested to maximize the possibility of obtaining correlation coeffecients based on change scores which are large and stable.
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Modelling of multi-state panel data : the importance of the model assumptionsMafu, Thandile John 12 1900 (has links)
Thesis (MCom)--Stellenbosch University, 2014. / ENGLISH ABSTRACT: A multi-state model is a way of describing a process in which a subject moves through a series
of states in continuous time. The series of states might be the measurement of a disease for
example in state 1 we might have subjects that are free from disease, in state 2 we might have
subjects that have a disease but the disease is mild, in state 3 we might have subjects having a
severe disease and in last state 4 we have those that die because of the disease. So Markov
models estimates the transition probabilities and transition intensity rates that describe the
movement of subjects between these states. The transition might be for example a particular
subject or patient might be slightly sick at age 30 but after 5 years he or she might be worse.
So Markov model will estimate what probability will be for that patient for moving from state
2 to state 3.
Markov multi-state models were studied in this thesis with the view of assessing the Markov
models assumptions such as homogeneity of the transition rates through time, homogeneity of
the transition rates across the subject population and Markov property or assumption.
The assessments of these assumptions were based on simulated panel or longitudinal dataset
which was simulated using the R package named msm package developed by Christopher
Jackson (2014). The R code that was written using this package is attached as appendix.
Longitudinal dataset consists of repeated measurements of the state of a subject and the time
between observations. The period of time with observations in longitudinal dataset is being
made on subject at regular or irregular time intervals until the subject dies then the study ends. / AFRIKAANSE OPSOMMING: ’n Meertoestandmodel is ’n manier om ’n proses te beskryf waarin ’n subjek in ’n ononderbroke
tydperk deur verskeie toestande beweeg. Die verskillende toestande kan byvoorbeeld vir die
meting van siekte gebruik word, waar toestand 1 uit gesonde subjekte bestaan, toestand 2 uit
subjekte wat siek is, dog slegs matig, toestand 3 uit subjekte wat ernstig siek is, en toestand 4
uit subjekte wat aan die siekte sterf. ’n Markov-model raam die oorgangswaarskynlikhede en
-intensiteit wat die subjekte se vordering deur hierdie toestande beskryf. Die oorgang is
byvoorbeeld wanneer ’n bepaalde subjek of pasiënt op 30-jarige ouderdom net lig aangetas is,
maar na vyf jaar veel ernstiger siek is. Die Markov-model raam dus die waarskynlikheid dat so
’n pasiënt van toestand 2 tot toestand 3 sal vorder.
Hierdie tesis het ondersoek ingestel na Markov-meertoestandmodelle ten einde die aannames
van die modelle, soos die homogeniteit van oorgangstempo’s oor tyd, die homogeniteit van
oorgangstempo’s oor die subjekpopulasie en tipiese Markov-eienskappe, te beoordeel.
Die beoordeling van hierdie aannames was gegrond op ’n gesimuleerde paneel of longitudinale
datastel wat met behulp van Christopher Jackson (2014) se R-pakket genaamd msm gesimuleer
is. Die R-kode wat met behulp van hierdie pakket geskryf is, word as bylae aangeheg. Die
longitudinale datastel bestaan uit herhaalde metings van die toestand waarin ’n subjek verkeer
en die tydsverloop tussen waarnemings. Waarnemings van die longitudinale datastel word met
gereelde of ongereelde tussenposes onderneem totdat die subjek sterf, wanneer die studie dan
ook ten einde loop.
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Informative drop-out models for longitudinal binary dataChau, Ka-ki., 周嘉琪. January 2003 (has links)
published_or_final_version / abstract / toc / Statistics and Actuarial Science / Master / Master of Philosophy
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