ijsmr

ijsmr logo-pdf 1349088093

Observation-Driven Model for Zero-Inflated Daily Counts of Emergency Room Visit Data
Pages 220-228
Gary Sneddon, Wasimul Bari and M. Tariqul Hasan
DOI:
http://dx.doi.org/10.6000/1929-6029.2013.02.03.7
Published: 31 July 2013


Abstract: Time series data with excessive zeros frequently occur in medical and health studies. To analyze time series count data without excessive zeros, observation-driven Poisson regression models are commonly used in the literature. As handling excessive zeros in count data is not straightforward, observation-driven models are rarely used to analyze time series count data with excessive zeros. In this paper an observation-driven zero-inflated Poisson (ZIP) model for time series count data is proposed. This approach can accommodate an autoregressive serial dependence structure which commonly appears in time series. The estimation of the model parameters by using the quasi-likelihood estimating equation approach is discussed. To estimate the correlation parameters of the dependence structure, a moment approach is used. The proposed methodology is illustrated by applying it to a data set of daily emergency room visits due to bronchitis.

Keywords: Autocorrelation structure, non-stationary, observation-driven model, quasi-likelihood, zero-inflated Poisson.
Download Full Article

ijsmr logo-pdf 1349088093

Efficiency of Co-Expression of Transcription Factors Pdx1, Ngn3, NeuroD and Pax6 with Insulin: A Statistical Approach
Pages 229-238
Örjan Hallberg
DOI:
http://dx.doi.org/10.6000/1929-6029.2013.02.03.8
Published: 31 July 2013Open Access


Abstract:  Aim:The objective of this study was to investigate the time related profile and efficiency of co-expression of the homeodomain proteins Pdx1, NeuroD, Ngn3, Pax6 and caspase3 with insulin, and to establish the time periods post PDL optimum for islets transplantation.

Study Design/Methods: In this experimental study, immunofluorescent staining procedure was performed on deparaffinized pancreatic duct ligated (PDL) tissues of 78 Sprague–Dawley rats. Quantification of protein coexpression was made using a computerized morphometry. The efficiency of co-expression was arbitrary defined by the value of mean ratio (score without unit) of insulin expression divided by each expression index of the other proteins, occurring within the time interval of 12–24 h post PDL. Statistical tool was used to analyze the efficiency of co-expression of proteins; analysis of variances (one way ANOVA) was used to compare the means of co-expression indexes across the time periods pre- and post PDL. P-values less than 0.05 were considered statistically significant; no post hoc test was done.

Results: The curve of insulin expression showed a crossover with that of the co-expression at different time periods pre- and post PDL. The optimal or higher efficiency of co-expression was observed for insulin and Ngn3 co-expression, while a good or medium efficiency was noted for the co-expression of insulin with Pdx1, insulin with NeuroD and insulin with Pax6. Low or weak efficiency was observed for the co-expression of insulin with caspase3.

Conclusion: We therefore propose an early islets transplantation using 12–24 h post PDL harvested pancreatic tissues.

Keywords: Islets, insulin, pancreas, duct ligation, transplantation, protein expression.
Download Full Article

ijsmr logo-pdf 1349088093

The Methodology of Human Diseases Risk Prediction Tools
Pages 239-248
H. Mannan, R. Ahmed, M. Sanagou, S. Ivory and R. Wolfe
DOI:
http://dx.doi.org/10.6000/1929-6029.2013.02.03.9
Published: 31 July 2013


Abstract: Disease risk prediction tools are used for population screening and to guide clinical care. They identify which individuals have particularly elevated risk of disease. The development of a new risk prediction tool involves several methodological components including: selection of a general modelling framework and specific functional form for the new tool, making decisions about the inclusion of risk factors, dealing with missing data in those risk factors, and performing validation checks of a new tool’s performance. There have been many methodological developments of relevance to these issues in recent years. Developments of importance for disease detection in humans were reviewed and their uptake in risk prediction tool development illustrated. This review leads to guidance on appropriate methodology for future risk prediction development activities.

Keywords: Disease risk prediction, missing data, model validation, model updating, model utility.
Download Full Article