Statistical modelling for falls count data
- Ullah, Shahid, Finch, Caroline, Day, Lesley
- Authors: Ullah, Shahid , Finch, Caroline , Day, Lesley
- Date: 2010
- Type: Text , Journal article
- Relation: Accident Analysis and Prevention Vol. 42, no. 2 (2010), p. 384-392
- Relation: http://purl.org/au-research/grants/nhmrc/565900
- Full Text:
- Reviewed:
- Description: Falls and their injury outcomes have count distributions that are highly skewed toward the right with clumping at zero, posing analytical challenges. Different modelling approaches have been used in the published literature to describe falls count distributions, often without consideration of the underlying statistical and modelling assumptions. This paper compares the use of modified Poisson and negative binomial (NB) models as alternatives to Poisson (P) regression, for the analysis of fall outcome counts. Four different count-based regression models (P, NB, zero-inflated Poisson (ZIP), zero-inflated negative binomial (ZINB)) were each individually fitted to four separate fall count datasets from Australia, New Zealand and United States. The finite mixtures of P and NB regression models were also compared to the standard NB model. Both analytical (F, Vuong and bootstrap tests) and graphical approaches were used to select and compare models. Simulation studies assessed the size and power of each model fit. This study confirms that falls count distributions are over-dispersed, but not dispersed due to excess zero counts or heterogeneous population. Accordingly, the P model generally provided the poorest fit to all datasets. The fit improved significantly with NB and both zero-inflated models. The fit was also improved with the NB model, compared to finite mixtures of both P and NB regression models. Although there was little difference in fit between NB and ZINB models, in the interests of parsimony it is recommended that future studies involving modelling of falls count data routinely use the NB models in preference to the P or ZINB or finite mixture distribution. The fact that these conclusions apply across four separate datasets from four different samples of older people participating in studies of different methodology, adds strength to this general guiding principle. © 2009 Elsevier Ltd. All rights reserved.
- Authors: Ullah, Shahid , Finch, Caroline , Day, Lesley
- Date: 2010
- Type: Text , Journal article
- Relation: Accident Analysis and Prevention Vol. 42, no. 2 (2010), p. 384-392
- Relation: http://purl.org/au-research/grants/nhmrc/565900
- Full Text:
- Reviewed:
- Description: Falls and their injury outcomes have count distributions that are highly skewed toward the right with clumping at zero, posing analytical challenges. Different modelling approaches have been used in the published literature to describe falls count distributions, often without consideration of the underlying statistical and modelling assumptions. This paper compares the use of modified Poisson and negative binomial (NB) models as alternatives to Poisson (P) regression, for the analysis of fall outcome counts. Four different count-based regression models (P, NB, zero-inflated Poisson (ZIP), zero-inflated negative binomial (ZINB)) were each individually fitted to four separate fall count datasets from Australia, New Zealand and United States. The finite mixtures of P and NB regression models were also compared to the standard NB model. Both analytical (F, Vuong and bootstrap tests) and graphical approaches were used to select and compare models. Simulation studies assessed the size and power of each model fit. This study confirms that falls count distributions are over-dispersed, but not dispersed due to excess zero counts or heterogeneous population. Accordingly, the P model generally provided the poorest fit to all datasets. The fit improved significantly with NB and both zero-inflated models. The fit was also improved with the NB model, compared to finite mixtures of both P and NB regression models. Although there was little difference in fit between NB and ZINB models, in the interests of parsimony it is recommended that future studies involving modelling of falls count data routinely use the NB models in preference to the P or ZINB or finite mixture distribution. The fact that these conclusions apply across four separate datasets from four different samples of older people participating in studies of different methodology, adds strength to this general guiding principle. © 2009 Elsevier Ltd. All rights reserved.
Applications of functional data analysis : A systematic review
- Ullah, Shahid, Finch, Caroline
- Authors: Ullah, Shahid , Finch, Caroline
- Date: 2013
- Type: Text , Journal article
- Relation: BMC Medical Research Methodology Vol. 13, no. 43 (2013), p.1-12
- Relation: http://purl.org/au-research/grants/nhmrc/565900
- Full Text:
- Reviewed:
- Description: Background Functional data analysis (FDA) is increasingly being used to better analyze, model and predict time series data. Key aspects of FDA include the choice of smoothing technique, data reduction, adjustment for clustering, functional linear modeling and forecasting methods. Methods A systematic review using 11 electronic databases was conducted to identify FDA application studies published in the peer-review literature during 1995–2010. Papers reporting methodological considerations only were excluded, as were non-English articles. Results In total, 84 FDA application articles were identified; 75.0% of the reviewed articles have been published since 2005. Application of FDA has appeared in a large number of publications across various fields of sciences; the majority is related to biomedicine applications (21.4%). Overall, 72 studies (85.7%) provided information about the type of smoothing techniques used, with B-spline smoothing (29.8%) being the most popular. Functional principal component analysis (FPCA) for extracting information from functional data was reported in 51 (60.7%) studies. One-quarter (25.0%) of the published studies used functional linear models to describe relationships between explanatory and outcome variables and only 8.3% used FDA for forecasting time series data. Conclusions Despite its clear benefits for analyzing time series data, full appreciation of the key features and value of FDA have been limited to date, though the applications show its relevance to many public health and biomedical problems. Wider application of FDA to all studies involving correlated measurements should allow better modeling of, and predictions from, such data in the future especially as FDA makes no a priori age and time effects assumptions.
- Authors: Ullah, Shahid , Finch, Caroline
- Date: 2013
- Type: Text , Journal article
- Relation: BMC Medical Research Methodology Vol. 13, no. 43 (2013), p.1-12
- Relation: http://purl.org/au-research/grants/nhmrc/565900
- Full Text:
- Reviewed:
- Description: Background Functional data analysis (FDA) is increasingly being used to better analyze, model and predict time series data. Key aspects of FDA include the choice of smoothing technique, data reduction, adjustment for clustering, functional linear modeling and forecasting methods. Methods A systematic review using 11 electronic databases was conducted to identify FDA application studies published in the peer-review literature during 1995–2010. Papers reporting methodological considerations only were excluded, as were non-English articles. Results In total, 84 FDA application articles were identified; 75.0% of the reviewed articles have been published since 2005. Application of FDA has appeared in a large number of publications across various fields of sciences; the majority is related to biomedicine applications (21.4%). Overall, 72 studies (85.7%) provided information about the type of smoothing techniques used, with B-spline smoothing (29.8%) being the most popular. Functional principal component analysis (FPCA) for extracting information from functional data was reported in 51 (60.7%) studies. One-quarter (25.0%) of the published studies used functional linear models to describe relationships between explanatory and outcome variables and only 8.3% used FDA for forecasting time series data. Conclusions Despite its clear benefits for analyzing time series data, full appreciation of the key features and value of FDA have been limited to date, though the applications show its relevance to many public health and biomedical problems. Wider application of FDA to all studies involving correlated measurements should allow better modeling of, and predictions from, such data in the future especially as FDA makes no a priori age and time effects assumptions.
The Development of the Lunchtime Enjoyment of Activity and Play Questionnaire
- Hyndman, Brendon, Telford, Amanda, Finch, Caroline, Ullah, Shahid, Benson, Amanda
- Authors: Hyndman, Brendon , Telford, Amanda , Finch, Caroline , Ullah, Shahid , Benson, Amanda
- Date: 2013
- Type: Text , Journal article
- Relation: Journal of School Health Vol. 83, no. 4 (2013), p. 256-264
- Full Text:
- Reviewed:
- Description: Background: Enjoyment of physical activity is as an important determinant of children's participation in physical activity. Despite this, there is an absence of reliable measures for assessing children's enjoyment of play activities during school lunchtime. The purpose of this study was to develop and assess the reliability of the Lunchtime Enjoyment of Activity and Play (LEAP) Questionnaire. Methods: Questionnaire items were categorized employing a social-ecological framework including intrapersonal (20 items), interpersonal (2 items), and physical environment/policy (17 items) components to identify the broader influences on children's enjoyment. An identical questionnaire was administered on 2 occasions, 10days apart, to 176 children aged 8-12years, attending a government elementary school in regional Victoria, Australia. RESULTS: Test-retest reliability confirmed that 35 of 39 LEAP Questionnaire items had at least moderate kappa agreement ranging from .44 to .78. Although 4 individual kappa values were low, median kappa scores for each aggregated social-ecological component reached at least moderate agreement (.44-.60). Conclusions: This study confirms the LEAP Questionnaire to be a reliable, context-specific instrument with sound content, and face validity that employs a social-ecological framework to assess children's enjoyment of school play and lunchtime activities. © 2013, American School Health Association.
- Description: 2003010857
- Authors: Hyndman, Brendon , Telford, Amanda , Finch, Caroline , Ullah, Shahid , Benson, Amanda
- Date: 2013
- Type: Text , Journal article
- Relation: Journal of School Health Vol. 83, no. 4 (2013), p. 256-264
- Full Text:
- Reviewed:
- Description: Background: Enjoyment of physical activity is as an important determinant of children's participation in physical activity. Despite this, there is an absence of reliable measures for assessing children's enjoyment of play activities during school lunchtime. The purpose of this study was to develop and assess the reliability of the Lunchtime Enjoyment of Activity and Play (LEAP) Questionnaire. Methods: Questionnaire items were categorized employing a social-ecological framework including intrapersonal (20 items), interpersonal (2 items), and physical environment/policy (17 items) components to identify the broader influences on children's enjoyment. An identical questionnaire was administered on 2 occasions, 10days apart, to 176 children aged 8-12years, attending a government elementary school in regional Victoria, Australia. RESULTS: Test-retest reliability confirmed that 35 of 39 LEAP Questionnaire items had at least moderate kappa agreement ranging from .44 to .78. Although 4 individual kappa values were low, median kappa scores for each aggregated social-ecological component reached at least moderate agreement (.44-.60). Conclusions: This study confirms the LEAP Questionnaire to be a reliable, context-specific instrument with sound content, and face validity that employs a social-ecological framework to assess children's enjoyment of school play and lunchtime activities. © 2013, American School Health Association.
- Description: 2003010857
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