Using latent class analysis to model prescription medications in the measurement of falling among a community elderly population

Hardigan, Patrick C.; Schwartz, David C.; Hardigan, W. D.

doi:10.1186/1472-6947-13-60

Cited by 5 publications

(3 citation statements)

References 16 publications

(17 reference statements)

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“…In either case, membership in identified classes is mutually exclusive, such that each observation is classified into only one of the identified classes. While it is straightforward to implement (Hibbard et al, 2007 ; Reinke et al, 2008 ; Archambault et al, 2009 ; Hardigan, 2009 ), this strategy comes with some critical disadvantages. First, there can be misclassified individuals, because deterministic classifications are based on the probabilistic information of class-membership probabilities.…”

Section: Methods To Two-phase Mixture Modelsmentioning

confidence: 99%

Evaluation of Analysis Approaches for Latent Class Analysis with Auxiliary Linear Growth Model

et al. 2018

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This study investigated the performance of three selected approaches to estimating a two-phase mixture model, where the first phase was a two-class latent class analysis model and the second phase was a linear growth model with four time points. The three evaluated methods were (a) one-step approach, (b) three-step approach, and (c) case-weight approach. As a result, some important results were demonstrated. First, the case-weight and three-step approaches demonstrated higher convergence rate than the one-step approach. Second, it was revealed that case-weight and three-step approaches generally did better in correct model selection than the one-step approach. Third, it was revealed that parameters were similarly recovered well by all three approaches for the larger class. However, parameter recovery for the smaller class differed between the three approaches. For example, the case-weight approach produced constantly lower empirical standard errors. However, the estimated standard errors were substantially underestimated by the case-weight and three-step approaches when class separation was low. Also, bias was substantially higher for the case-weight approach than the other two approaches.

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Section: Methods To Two-phase Mixture Modelsmentioning

confidence: 99%

Evaluation of Analysis Approaches for Latent Class Analysis with Auxiliary Linear Growth Model

et al. 2018

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“…Young adult consumers wine behaviour regarding wine. Relevant measures were used to determine the optimal number of clusters, namely the BIC criteria (Nylund et al, 2007) and the χ 2 statistics (Hardigan et al, 2013). The "p-value" column provides the p-value for each model under the assumption that the G² statistic follows a χ 2 distribution.…”

mentioning

confidence: 99%

Subjective knowledge as a determinant of young adult consumers wine behaviour

Hristov

Kuhar

2015

British Food Journal

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Purpose – The purpose of this paper is to provide additional insight into how the level of subjective knowledge (SK) related to wine explains differences in the wine-consumption behaviour of young adults. Particular attention was given to information search strategies employed by young adult wine consumers. Design/methodology/approach – A web-based survey was carried out on 287 young urban wine consumers who were recruited in specialised wine shops and at wine festivals. The key variables presenting the consumers’ wine searches were measured using the best-worst scaling method. Latent class cluster analysis (LCA) was used to segment the respondents into clusters based on their level of SK of wine. Findings – The study identifies three consumer segments with corresponding levels of SK related to wine. The segments present considerable differences in the wine-consumption-related behaviours and information search strategies. Research limitations/implications – Understanding young adults’ SK of wine will assist wine marketers in their efforts to establish marketing strategies for this generational cohort. In addition, research (preferably transnational) is recommended to validate the conclusions and to gain additional understanding of SK as an indicator of wine-related behaviours. Originality/value – This study contributes to a better understanding of the wine-purchasing behaviours of young adults with particular focus on SK related to wine. The results obtained may be applied by winemakers in the development of marketing and promotion strategies geared towards the promising young adult consumer segment.

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“…Cluster analysis is seldom applied to population based epidemiological studies due to its less intuitive results compared to regression-based methods, but has already shown promising results [ 3 , 5 , 27 ]. Hurault-Delarue and co-authors [ 3 ] used an extension of the traditional k-means algorithm to longitudinal data to simultaneously examine the intensity and timing of exposure to psychotropic medications during pregnancy, where the intensity of the medication use was determined by using the estimated DDD from the French prescription database.…”

Section: Discussionmentioning

confidence: 99%

Complex patterns of concomitant medication use: A study among Norwegian women using paracetamol during pregnancy

Salvatore¹,

Domańska²,

Wood³

et al. 2017

PLoS ONE

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BackgroundStudies on medication safety in pregnancy often rely on an oversimplification of medication use into exposed or non-exposed, without considering intensity and timing of use in pregnancy, or concomitant medication use. This study uses paracetamol in pregnancy as the motivating example to introduce a method of clustering medication exposures longitudinally throughout pregnancy. The aim of this study was to use hierarchical cluster analysis (HCA) to better identify clusters of medication exposure throughout pregnancy.MethodsData from the Norwegian Mother and Child Cohort Study was used to identify subclasses of women using paracetamol during pregnancy. HCA with customized distance measure was used to identify clusters of medication exposures in pregnancy among children at 18 months.ResultsThe pregnancies in the study (N = 9 778) were grouped in 5 different clusters depending on their medication exposure profile throughout pregnancy.ConclusionUsing HCA, we identified and described profiles of women exposed to different medications in combination with paracetamol during pregnancy. Identifying these clusters allows researchers to define exposure in ways that better reflects real-world medication usage patterns. This method could be extended to other medications and used as pre-analysis for identifying risks associated with different profiles of exposure.

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Using latent class analysis to model prescription medications in the measurement of falling among a community elderly population

Cited by 5 publications

References 16 publications

Evaluation of Analysis Approaches for Latent Class Analysis with Auxiliary Linear Growth Model

Evaluation of Analysis Approaches for Latent Class Analysis with Auxiliary Linear Growth Model

Subjective knowledge as a determinant of young adult consumers wine behaviour

Complex patterns of concomitant medication use: A study among Norwegian women using paracetamol during pregnancy

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