We consider the problem of outlier detection in bivariate exponential data fitted using the generalized linear model via Bayesian approach. We follow closely the work outlined by Unnikrishnan (2010) and present every step of the detection procedure in details. Due to the complexity of the resulting joint posterior distribution, we obtain the information on the posterior distribution from samples generated by Markov Chain Monte Carlo sampling, in particular, using either the Gibbs sampler or the Metropolis-Hastings algorithm. We use local breast cancer patients’ data to illustrate the implementation of the method.
A cylindrical data set consists of circular and linear variables. We focus on developing an outlier detection procedure
for cylindrical regression model proposed by Johnson and Wehrly (1978) based on the k-nearest neighbour approach.
The procedure is applied based on the residuals where the distance between two residuals is measured by the Euclidean
distance. This procedure can be used to detect single or multiple outliers. Cut-off points of the test statistic are generated
and its performance is then evaluated via simulation. For illustration, we apply the test on the wind data set obtained
from the Malaysian Meteorological Department.
Introduction: Monitoring changes in energy and nutrient intakes of the population
over the course of time is essential to help healthcare providers develop effective
dietary policies. The aim of this study was to assess the changes in the nutrient
intake and Recommended Nutrient Intake (RNI) achievements by using the data
obtained from the Malaysian Adult Nutrition Surveys (MANS) that were carried out
in 2003 and 2014. Mis-reporting of energy intake was taken into account. Methods:
Dietary data were obtained from MANS 2003 and MANS 2014, which involved a
combined total of 4,044 randomly selected respondents, aged 18-59 years, using
a single 24-hour diet recall. Energy and nutrients calculations were based on the
Malaysian Food Composition database using the Nutritionist Pro software. The
results were compared against the RNI for Malaysia to assess dietary adequacy.
Results: The proportions of calories derived from macronutrients were within the
recommendations for a healthy diet. The consumption of protein, fat, calcium, iron
and vitamin A was significantly higher in 2014 than in 2003. The consumption
of protein, iron, vitamin C, and vitamin A was found to exceed the RNIs in 2014.
However, carbohydrate and sodium intakes had significantly decreased. Despite the
decrease, sodium intake still exceeded RNI recommendations. Conclusion: Signs
of changing energy and nutrient intakes were found, including increases in protein
and fat intakes since 2003, and decreased carbohydrates. This could be an alarming
indicator of the tendency to eat energy dense food among the population.
Introduction: Under-reporting of energy intake is a common cause of bias
in nutritional studies. This study was aimed at examining the extent of underreporting of energy intake and its related characteristics among respondents in
the Malaysian Adult Nutrition Survey (MANS) 2003 and MANS 2014. Methods:
The present study analysed energy intakes of 9,624 adults aged 18-59 years from
the MANS in year 2014 (2,890 respondents) and 2003 (6,734 respondents) using
a single 24-hour diet recall. Basal metabolic rates (BMR) were calculated from the
age- and gender-specific equations of Schofield. Under-reporting was defined as an
energy intake:BMR ratio of