Multivariate Multilevel Modeling of Age Related Diseases

The emerging role of modeling multivariate multilevel data in the context of analyzing the risk factors are examined for the severity of cardiovascular disease diabetes, and chronic respiratory conditions. The modeling phase results leads to some important interaction terms between blood glucose, blood pressure, obesity, smoking and alcohol to the mortality rates

Fiber Based Approaches as Medicine Delivery Systems

The goal of drug delivery is to ensure that therapeutic molecules reach the intended target organ or tissue, such that the effectiveness of the drug is maximized. The efficiency of a drug delivery system greatly depends on the choice of drug carrier. Recently, there has been growing interest in using micro- and nanofibers for this purpose. The reasons for this growing interest include these materials’ high surface area to volume ratios, ease of fabrication, high mechanical properties, and desirable drug release profile. Here, we review developments in using these materials made by the most prevalent methods of fiber fabrication: electrospinning, microfluidics, wet spinning, rotary spinning, and self-assembly for drug delivery purposes. Additionally, we discuss the potential to use these fiber based systems in research and clinical applications

The use of interim inspections for making decisions and testing assumptions in clinical trials

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Information technology usage in building operation and maintenance management

Information Technology (IT) is identified as rapidly evolving field in the world which radically changed the way most professions operate in recent past. IT has widely practice among various professions to maximize the effectiveness, efficiency of their work. This is equally applicable to professionals involved in building operations and Maintenance management. Thus this study aims to explore current IT usage in building operation and maintenance management in commercial buildings of Sri Lanka. Accordingly the study was an exploratory research carried out through survey approach. Survey consists of 27 commercial buildings covering hotels, office buildings, and hospitals and shopping complexes in Colombo. Semi structured interviews used as the data collection technique and descriptive analysis techniques used analysis the survey findings. Findings revealed that Building Management System (BMS) as the only IT based system which used for building operation and maintenance management where most functions are carried out use of general software such as spreadsheet and word processor due to financial. budgeting problems. This study enabled to identify the IT usage in building operation and maintenance management highlighting the loopholes which need to address for effective and efficient building operation and maintenance management

Incorporating intermediate binary responses into interim analyses of clinical trials : a comparison of four methods.

In clinical trials with a long period of time between randomization and the primary assessment of the patient, the same assessments are often undertaken at intermediate times. When an interim analysis is conducted, in addition to the patients who have completed the primary assessment, there will be those who have till then undergone only intermediate assessments. The efficiency of the interim analysis can be increased by the inclusion of data from these additional patients. This paper compares four methods of increasing information based on model-free estimates of transition probabilities to incorporate intermediate assessments from patients who have not completed the trial. It is assumed that the observations are binary and that there is one intermediate assessment. The methods are the score and Wald approaches, each with the log-odds ratio and probability difference parameterizations. Simulations show that all four approaches have good properties in moderate to large sample sizes

Generalized Linear Multilevel Models for Ordinal Categorical Responses: Methods and Application to Medical Data

Statistical modeling of multilevel data has been in discussion for several years and many developments have been made in this aspect. However the field of multilevel modeling for discrete categorical responses is relatively new, with markedly few applications in the areas of ordinal categorical response modeling. Most of these applications are focused in the area of educational data. The basis of this paper is to explore the use of Generalized Linear Multilevel Models for modeling a multilevel ordinal categorical response, in the field of medicine, which is somewhat of a novel application, as these methods have seldom been utilized in modeling medical data. The application focuses on analysing the factors that affect the severity of respiratory infections diagnosed in family practice and is based on data collected at 13 family practices in Sri Lanka. The data consisted of individual patient records, clustered within the practices and thus required a multilevel modeling approach. The explanatory variables pertaining to this study were: Age, Gender, Duration and most prevailing Symptom of the patients, while the ordinal categorical response indicating the severity of the diagnosis made was termed Diagnosis. Two main approaches of the Generalized Linear Multilevel Model; namely the Proportional Odds Model and the Non-Proportional Odds Model have been applied to the data and the models compared using suitable diagnostic tests. The variables Symptom and Duration provided significant main effects while the Symptom-Gender interaction also proved to be significant. Based on the DIC diagnostic, the Non-Proportional Odds model proves to be the better of the two models

PRESENT STATUS OF BIOFERTILIZER USAGE AND PROSPECTS OF BIOFERTILIZER MARKETING AMONG SMALL ORGANIC TEA GROWERS (A CASE STUDY IN GAMPOLA)

Bio-fertilizer is a large population of a specific or a group of beneficial microorganisms which enhance the soil productivity. Biofertilizer usage is mainly concentrated on organic tea cultivation in Sri Lanka. The objectives of the study were; to examine the present status of biofertilizer usage among small organic tea growers; to ascertain their attitudes, to analyze constraints of promoting biofertilizer; and to make recommendations to mprove the biofertilizer marketing. The study was conducted through a field survey and informal discussions. 75% of small organic tea growers use commercially produced biofertilizers. Biofertilizer users obtain a significant higher yield than non-users of bio-fertilizer. The growers showed significant positive perception on the yielding ability, ability to enhance soil fertility, less environment pollution caused by biofertilizers. Lack of subsidies, government support, information and knowledge are the main constraints of promoting biofertilizers. Policy issues on biofertilizer subsidies, workshops, awareness programmes and field demonstrations, financial support for producers from the government can be recommended to improve the biofertilizer marketing among small organic tea growers.For full paper: [email protected]

Generalized linear multilevel models for ordinal categorical responses: methods and application to medical data

Statistical modeling of multilevel data has been in discussion for several years and many developments have been made in this aspect. However the field of multilevel modeling for discrete categorical responses is relatively new, with markedly few applications in the areas of ordinal categorical response modeling. Most of these applications are focused in the area of educational data. The basis of this paper is to explore the use of Generalized Linear Multilevel Models for modeling a multilevel ordinal categorical response, in the field of medicine, which is somewhat of a novel application, as these methods have seldom been utilized in modeling medical data. The application focuses on analysing the factors that affect the severity of respiratory infections diagnosed in family practice and is based on data collected at 13 family practices in Sri Lanka. The data consisted of individual patient records, clustered within the practices and thus required a multilevel modeling approach. The explanatory variables pertaining to this study were: Age, Gender, Duration and most prevailing Symptom of the patients, while the ordinal categorical response indicating the severity of the diagnosis made was termed Diagnosis. Two main approaches of the Generalized Linear Multilevel Model; namely the Proportional Odds Model and the Non-Proportional Odds Model have been applied to the data and the models compared using suitable diagnostic tests. The variables Symptom and Duration provided significant main effects while the Symptom-Gender interaction also proved to be significant. Based on the DIC diagnostic, the Non-Proportional Odds model proves to be the better of the two models

Generalized cochran mantel haenszel test for multilevel correlated categorical data: An algorithm and R function

Multilevel data are a commonly encountered phenomenon in many data structures. Modelling such data requires careful consideration of the association between underlying variables at each level of the data structure. This requires the use of effective univariate techniques prior to modelling. However, currently no univariate tests are used to handle this situation. This paper presents the modification and novel application of a test developed by Zhang and Boos for testing the association between categorical variables measured on clusters of observations, for examining initial association in a multilevel framework. Zhang and Boos have used a SAS/IML programme (unpublished) for performing their test. This paper presents an R function for the application of the test, which will be freely available to users, since R is an open source software. The function is tested on a dataset from the medical field pertaining to respiratory disease severity of patients, attending several different clinics. The explanatory variables pertaining to this study are Age, Gender, Duration and Symptom, while the response variable indicating the severity of the diagnosis made is termed Diagnosis. The results indicate that when the experimental units show low levels of correlation within clusters with respect to a particular explanatory variable, the test performs similarly to the Standard Cochran Mantel Haenszel (CMH) test. When the corresponding correlation is high, the Generalized CMH (GCMH) test results in a smaller p-value than the Standard CMH test. Of the four variables, only Symptom and Duration are significant with respect to association with Diagnosis

Incorporating data received after a sequential trial has stopped into the final analysis: implementation and comparison of methods

In a sequential clinical trial, accrual of data on patients often continues after the stopping criterion for the study has been met. This is termed “overrunning.” Overrunning occurs mainly when the primary response from each patient is measured after some extended observation period. The objective of this article is to compare two methods of allowing for overrunning. In particular, simulation studies are reported that assess the two procedures in terms of how well they maintain the intended type I error rate. The effect on power resulting from the incorporation of “overrunning data” using the two procedures is evaluated