| No. of records per page: 10 | 20 | 30 | 50 | 100 | Show all |
Record ID: 60 [ Page 6 of 8, No. 1 ]
Biosurveillance of measles using control charts: A case study using NCR laboratory confirmed measles counts from January 2009 to January 2014
Authors: Lorraine Christelle B. Angkico; Priscilla A. Diaz; Robert Neil F. Leong; Frumencio F. Co
Abstract:
This paper aims to explore early outbreak detection methods for measles. Two methods adopted from statistical process control were modified and used to fit biosurveillance, namely Shewhart and Exponentially Weighted Moving Average (EWMA) charts. Seven variations of such control charts are proposed: two under Shewhart chart (normal-based and zero-inflated Poisson (ZIP)-based) and five under EWMA charts (?s of 0.05, 0.10, 0.15, 0.20, and 0.25). To study the proposed charts, daily counts of laboratory confirmed cases of measles in the National Capital Region from 2009 until 2014 were utilized to characterize both the disease background and outbreak equations. During this time span, three measles outbreaks have transpired. The proposed charts, set at average time between false signals (ATFSs) of both one and two months, were evaluated and compared using performance metrics such as conditional expected delay (CED), proportion of true signals (PTS), proportions of detections in an outbreak (PDO), and probability of successful detection (PSD), computed from 500 sets of simulated data. It was found that ZIP-based Shewhart and EWMA with a ? of 0.05 work best for ATFSs of one and two months, respectively. Health-governing bodies may seek to explore the possible utilization of these charts to improve measles surveillance.
Keywords: control charts, measles, early event detection, biosurveillance
Download this article:
Year: 2014 Vol.: 63 No.: 2
Record ID: 59 [ Page 6 of 8, No. 2 ]
An efficient variant of dual to ratio and product estimator in sample surveys
Authors: Gajendra K. Vishwakarma; Raj K. Gangele; Ravendra Singh
Abstract:
In this paper, we propose a dual to ratio and product estimator for estimating finite population mean of study variable on applying simple transformation to auxiliary variable by using its average values in the population that are generally available in practice. The mean squared error of the proposed estimator have been obtained to the first degree of approximation. It has also been shown that the proposed estimator has greater applicability and is more efficient than the usual estimator even when, the existing estimators are less efficient. An empirical study is carried out to demonstrate the performance of proposed estimator.
Keywords: Auxiliary variable, Study variable, Mean square error, Population mean, Simple random sampling
Download this article:
Year: 2014 Vol.: 63 No.: 2
Record ID: 58 [ Page 6 of 8, No. 3 ]
A general class of chain ratio-product type exponential estimators in double sampling using two auxiliary variates
Authors: Gajendra K. Vishwakarma; Manish Kumar; Raj K. Gangele
Abstract:
In this paper, a general class of chain ratio-product type exponential estimators has been proposed for estimating a finite population mean in presence of two auxiliary variates under double sampling scheme. The expressions for bias and mean square error (MSE) of the proposed class are derived up to the first degree of approximation. Also, the expression of asymptotic optimum estimator (AOE) in the proposed class is obtained. Some estimators are shown to be particular members of the proposed class. The proposed class has been compared for its precision with the usual unbiased estimator and several other estimators of the literature. In addition, an empirical study is also carried out in support of theoretical findings.
Keywords: Auxiliary variates, Study variate, Double Sampling, bias, mean square error.
Download this article:
Year: 2014 Vol.: 63 No.: 2
Record ID: 57 [ Page 6 of 8, No. 4 ]
Modeling clustered survival data with cured fraction
Authors: Iris Ivy M. Gauran; Angela D. Nalica
Abstract:
In modelling lifetime data, standard parametric theory assumes that all observations will eventually experience the event of interest if they are monitored for a very long period. While every unit starts as susceptible to the event of interest, a fraction of observations may switch into a non-susceptible group. A mixture cured fraction model with covariates is modified to incorporate random clustering effect to characterize the switch mechanism. Simulation studies and telecommunications data show that cured fraction models with random clustering effect perform better than their parametric counterpart in terms of predictive ability. Moreover, results show that the nonparametric method is superior than modified parametric Cox PH model.
Keywords: Mixture Cured Fraction Models, Random Clustering Effect, Right-censored Lifetime Data
Download this article:
Year: 2014 Vol.: 63 No.: 2
Record ID: 56 [ Page 6 of 8, No. 5 ]
Proceedings of the Focused Group Discussion on Accreditation/Certification for Professional Statisticians
Authors: PSAI Initiatives
Abstract:
FOREWORD
The Philippine Statistical Association, Inc. (PSAI) is a professional association dedicated to the promotion of Statistics as a science and a discipline. As such, it recognizes the need to pursue the development of the discipline and the continuing professional growth of its practitioners in the academe, the government and private sectors, and in the international community.
In 2008, the PSAI through the Institutional Development Committee (IDC) chaired by Mr. Tomas P. Africa, then Vice President and Chair of the IDC pursued the crafting and ratification of the Code of Ethics for Statisticians, and notes in the Foreword that:
"It has been an aspiration of the Philippine Statistical Association (PSA) to institute a system of accreditation or certification for Statistics professionals, similar to those existing in Australia, New Zealand, the United Kingdom and the United States. On at least two fronts, the label 'statistician' may have been misused and misappropriated by unscrupulous professionals.
The accreditation stage will deal with what would be the qualifications: education, work experience, research record as well as the behavior or ethical standards of the statistics practitioner. This Code addresses the latter. The necessary academic background, and work experience needed to bring about the conduct and/or behavior of such professionals may be deduced from this Code."
With the Code of Ethics for Statisticians firmly in place, the stage is set for the accreditation process. Under the same stewardship, Mr. Africa as Vice President and Chair of the Institutional Development Committee (2012-2013), concerned professionals were gathered to undertake the Focus Group Discussion (FGD), and to put into motion the work envisioned to initiate the development of a system for eventual accreditation and professional certification of practitioners in the statistics profession.
Keywords:
Download this article:
Year: 2014 Vol.: 63 No.: 1
Record ID: 55 [ Page 6 of 8, No. 6 ]
Indentifying Influencers of Consumer Activity: A Case Study in Predictive Modeling
Authors: Angela D. Nalica; Joseph Ryan G. Lansangan
Abstract:
Marketing activation usually entails a universal blast of information to all consumers. Oftentimes, only a small proportion of the consumers react positively to such activation, resulting to waste in marketing expenses. If a circle of influencers can be identified for certain events or phenomena, then such activities can be focused into a group of factors or individuals, thus, optimizing the outcomes. With the identification of such group of influencers, resources for strategic optimization of outcomes can be allocated efficiently. A usage database is used to identify consumers who could initiate or influence the complex dynamics of consumer behavior. The data mining process of clustering, sampling, aggregation, modeling, and validation are used to mine such information from the database.
Keywords: logistic regression, segmentation, influencers, consumer behaviour, customer relationship management
Download this article:
Year: 2014 Vol.: 63 No.: 1
Record ID: 54 [ Page 6 of 8, No. 7 ]
Effects of Household Use of Biomass Fuel and Kerosene on Birth Weight of Babies in the Philippines
Authors: Michael Daniel C. Lucagbo
Abstract:
Birth weight is an important indicator of a child’s health status. It is a significant factor of his or her risk of mortality and morbidity. Infants with low birth weight have been shown to be 40 times more likely to die within the first 28 days of birth than normal birth weight infants. Moreover, low birth weight infants exhibit a much higher incidence of neurological impairment, gross and fine motor dysfunction and developmental delay. Instead of going down to reduce the incidence of child mortality (which is one of the Millennium Development Goals), the incidence of low birth weight in the Philippines has gone the opposite direction: rising from 20.3% in 2003 to 21.2% in 2008. This paper tackles the very serious issue of birth weight using data from the 2008 National Demographic and Health Survey (NDHS), and focuses on one important risk factor: type of cooking fuel used in the household. Using the ordinal logistic regression model, the study establishes that the use of dirty cooking fuel (biomass fuel or kerosene) for daily use of cooking and heating is a significant environmental risk factor of low birth weight. Moreover, the results also show that maternal smoking is significantly associated with the size of the child at birth. Other demographic factors that may be associated with low birth weight are examined as well. Information about the effect cooking fuel on birth weight should lead the government and policymakers to make clean cooking fuel available to Philippine households at a cheap cost.
Keywords: Low birth weight, biomass fuel, maternal smoking, ordinal logistic regression
Download this article:
Year: 2014 Vol.: 63 No.: 1
Record ID: 53 [ Page 6 of 8, No. 8 ]
Comparison of Different Methods of Constructing Housing Start Index in the Philippines
Authors: Felicidad Hebron
Abstract:
We investigate three methods of constructing housing start index with a fixed base year. In the Philippines, researchers and planners uses data on building permits to monitor construction sites where economic activities are expected to follow. Suppliers of construction materials such as cement, lumber, steel, among others, rely on these data for planning purposes. Other businesses like banks and food chains also use these data as proximate indicators of supply and demand for investment. A mixed model accounting the empirical relations between the index and other economic indicators they usually lead is used in the assessment of the index resulting from three different methods. There is a strong space-time association between the index and other indicators, confirming the relationship between the economic boom and housing start index. There is evidence that the index is capable of leading some key economic indicators.
Keywords: housing start index, leading indicators, mixed models
Download this article:
Year: 2014 Vol.: 63 No.: 1
Record ID: 52 [ Page 6 of 8, No. 9 ]
Design Strategies in Fitting a Nonlinear Model
Authors: Michael Van Supranes
Abstract:
Estimation of parameters in a nonlinear model depends on the distribution of data points along various levels of curvature in the function to be estimated. Using Monte Carlo simulation, an optimal allocation procedure for building stratified designs was derived. The optimal allocation procedure conforms well to a proportionality property, directly relating the number of observations with the total curvature and measure or length of the domain. The proportionality property can be used to easily construct an allocation procedure that is near the optimal. Stratification results were applied and explored on uniform designs. Simulation results show that strategic stratification can improve the prediction accuracy of uniform designs.
Keywords: Stratification, Experimental Designs, Spline Regression, Monte Carlo Simulation
Download this article:
Year: 2014 Vol.: 63 No.: 1
Record ID: 51 [ Page 6 of 8, No. 10 ]
Semiparametric Poisson Regression Model for Clustered Data
Authors: Eiffel A. de Vera
Abstract:
A semiparametric Poisson regression is proposed in modeling spatially clustered count data. The heterogeneous covariate effect across the clusters is formulated in the context of nonparametric regression while the random clustering effect is based on a parametric specification. We propose two estimation procedures: (1) the parametric and nonparametric parts are estimated simultaneously via penalized least squares; and (2) the parametric and nonparametric parts are estimated iteratively via the backfitting algorithm. The simulation study exhibited the advantages of these two methods over ordinary Poisson regression and an intrinsically linear model when the aggregate covariate effect is negligible. This happens when sensitivity to the covariate is minimal or the data-generating model is not linear. The two estimation methods are generally more advantageous over the traditional approaches when linear model fit is poor. In cases where the linear fit is good, the proposed methods are at par with the traditional methods, but the second approach can still be advantageous when there are several covariates involved since the backfitting algorithm yields computational simplicity in the estimation process.
Keywords: backfitting, generalized additive models, nonparametric regression, random effects
Download this article:
Year: 2014 Vol.: 63 No.: 1
Record ID: 50 [ Page 6 of 8, No. 11 ]
Modelling Zero-Inflated Clustered Count Data: A Semiparametric Approach
Authors: Kevin Carl P. Santos
Abstract:
This paper proposes to use an additive semiparametric Poisson regression in modelling zero-inflated clustered data. Two estimation methods are exploited in this paper based on de Vera (2010). The first simultaneously estimates both the parametric and nonparametric parts of the model. The second utilizes the backfitting algorithm by smoothing the nonparametric function of the covariates and then estimating the parametric parts of the postulated model. The predictive accuracy, measured in terms of root mean square error (RMSE), of the proposed methods is compared to that of ordinary Zero-Inflated Poisson (ZIP) regression model. It is found out through simulation study that the average RMSE of the ordinary ZIP regression model is at most 81% and 27% higher for equal and unequal cluster sizes, respectively, than that of proposed model whose parametric and nonparametric parts are simultaneously estimated.
Keywords: Zero-Inflated Poisson models, clustered data, Generalized Additive Models, backfitting algorithm
Download this article:
Year: 2014 Vol.: 63 No.: 1
Record ID: 49 [ Page 6 of 8, No. 12 ]
Autologistic Spatial-Temporal Modeling
Authors: Ma. Andriena Ida B. Del Ayre-Ofina
Abstract:
We postulate a combination of spatial-temporal and autologistic model in characterizing binary data collected over time and space. Using a second-order neighborhood system in defining the spatial component of the model, backfitting algorithm is used in estimating the model. As the incidence of success and failure responses becomes balanced, sensitivity and specificity increases. The predictive ability of the model is fairly robust to the spatial parameter but is significantly influenced by the temporal parameter. The bias of the estimate for the spatial parameter declines as it becomes dominant into the model. Furthermore, as the autocorrelation becomes stronger, its estimate becomes less biased. The backfitting algorithm is also observed to converge fast in the estimation of the spatial-temporal autologistic model.
Keywords: binary response, autologistic model, spatial-temporal model, backfitting
Download this article:
Year: 2014 Vol.: 63 No.: 1
Record ID: 48 [ Page 6 of 8, No. 13 ]
Visual Exploration of Climate Variability
Authors: Wendell Q. Campano; Rona Mae U. Tadlas
Abstract:
In this paper, a data visualization framework for investigating and exploring climate time series data is introduced. This method utilizes the results obtained from performing series of cluster analysis based on a particular multivariate data set for each defined subset in the time series. The said approach is implemented to the climate data in the Philippines. The data image results obtained from the procedure revealed the expected overall climate pattern in the Philippines as well as some localized segments of climate changes in the time series which deviate from the overall pattern. A wavelet analysis which is a well established method in analyzing climate data is also done to validate the results shown by the proposed visualization method.
Keywords: information visualization; data image; cluster analysis; wavelet; climate change; climate variability; time series; multivariate data
Download this article:
Year: 2013 Vol.: 62 No.: 2
Record ID: 47 [ Page 6 of 8, No. 14 ]
Measuring Income Mobility using Pseudo-Panel Data
Authors: Arturo M. Martinez Jr; Mark Western; Michele Haynes; Wojtek Tomaszewski
Abstract:
To reconcile the need of providing a more dynamic perspective of the evolution of income distribution with the lack of panel data, several techniques have been offered to construct pseudo-panel data from repeated cross-sectional surveys. Using actual panel data from the Philippines, this study evaluates the performance of four pseudo-panel techniques in measuring a wide array of income mobility indicators. Preliminary results suggest that methods with more flexible income model specifications perform better than those with highly parameterized models. More importantly, these flexible pseudo-panel procedures produced estimates of poverty dynamics and movement-based indices which are quite close to the estimates computed from the actual panel data. Nevertheless, further improvements are warranted to be able to develop a more satisfactory estimation procedure for indices measuring temporal dependence and the inequality-reducing effect of income mobility.
Keywords: panel survey; cross-sectional survey; temporal; dependence; income distribution
Download this article:
Year: 2013 Vol.: 62 No.: 2
Record ID: 46 [ Page 6 of 8, No. 15 ]
Effects of Education on Climate Risk Vulnerability in the Philippines: Evidence from Regional Panel Data
Authors: Michael Daniel C. Lucagbo; Kristina Norma B. Cobrador; Nikki Ann M. de Mesa; Remy Faye M. Ferrera; Jennifer E. Marasigan
Abstract:
The effects of climate change are being felt disproportionately in the world’s poorest countries and among those groups of people least able to cope. The Philippines, being a storm-lashed nation, is one country having high climate change vulnerability and low climate change resilience. A number of researches have suggested investments on adaptation which place strong emphasis on reducing vulnerability to climate change. Focusing on climate change vulnerability in the Philippines, this study examines the effect of one particular type of government intervention: increasing the level of education. In this study, the effect of education on vulnerability to climate change is examined in a regional panel data analysis using official Philippine statistics from the Natural Disaster Risk Reduction and Management Council (NDRRMC), Labor Force Survey (LFS), National Statistical Coordination Board (NSCB). Using the fixed-effects Poisson (FEP) regression model, the study establishes that at the community level, the number of employed college graduates is a significant factor that reduces climate risk vulnerability (measured by a number of deaths from natural disasters), controlling for other factors such as number of disasters, gross regional domestic product (GRDP), and population size.
Keywords: Vulnerability, Resilience, Panel Data, Fixed-effects Poisson model
Download this article:
Year: 2013 Vol.: 62 No.: 2
Record ID: 45 [ Page 6 of 8, No. 16 ]
Regression Analyses of the Philippine Birth Weight Distribution
Authors: Elline Jade Beltran; Robert Neil F. Leong; Frumencio F. Co
Abstract:
Low birth weight has both short-term and long-term effects. It can lead to complications among infants causing neonatal deaths. Several literatures also suggested relationships between low birth weight and delayed mental and physical development. These negative effects are further magnified in developing countries, one of which is the Philippines. In this paper, birth weight is analysed through logistic, ordinary least squares, and quantile regression techniques using a sample from the 2008 Philippine Birth Recode. Quantile regression results offer a more dynamic picture of how these correlates affect the conditional distribution of birth weight. The obtained estimates of the marginal effects of several demographical and maternal health correlates of birth weight suggest that socially and economically impoverished mothers are more likely to have low birth weight babies. These results would recommend a focus on improving maternal health care through proper education.
Keywords: birth weight; quantile regression; logistic regression; ordinary least squares
Download this article:
Year: 2013 Vol.: 62 No.: 2
Record ID: 44 [ Page 6 of 8, No. 17 ]
Profitability and Growth Topology Analysis of Unilevel-type of Network Marketing Structures
Authors: John Carlo P. Daquis; Angelique O. Castaneda; Nelson D. Sy; Joseph V. Abgona
Abstract:
This study analyzes a type of multi-level marketing (MLM) structure through a simulation of MLM systems. In unilevel MLM, distributors earn from both sales from direct selling and commissions from recruitment of downlines. Several distributional assumptions were made in constructing the system, such as the use of the uniform, Bernoulli, and Poisson distributions. Member income is measured based on commission from recruit pay-ins in their downlines and income from direct selling. Based on the simulated unilevel MLM structures, the fundamental behavior of a unilevel MLM is captured and analyzed in terms of its network growth topology and profitability.
Keywords: multi-level marketing; network simulation; unilevel structure; complex systems; probability distributions
Download this article:
Year: 2013 Vol.: 62 No.: 2
Record ID: 43 [ Page 6 of 8, No. 18 ]
Classification of Congenital Hypothyroidism using Artificial Neural Networks
Authors: Iris Ivy Gauran; Ma. Sofia Criselda A. Poblador
Abstract:
The Newborn Screening Reference Center (NSRC) of the National Health Institute in University of the Philippines Manila collects measurements from five attributes to determine whether Congenital Hypothyroidism (CH) is present in a neonate. Detecting the CH cases is a major concern of medical practitioners because it provides richer information than the healthy ones. However, because of the rarity of this metabolic condition, existing classification algorithms oftentimes misclassify a newborn as “normal” even if it is not. This paper investigates the efficiency of Self-Organizing Kohonen Maps (SOM), a type of artificial neural network. Though it is a visualization and clustering tool, the researchers want to probe on its ability to detect outliers and properly classify a newborn as normal or not by coming up with a statistically computed threshold value. Instead of working directly with the original attributes of the data, a reduced set of SOM prototypes is utilized to represent the data in a space of smaller dimension, seeking to preserve the probability distribution and topology of the input space. Results showed a misclassification rate of 13.5%. Though it is found to be slightly less superior to the existing classification rules, the proposed methodology was able to address the problem of finding a statistical threshold value. Also, the methodology verifies that age has a major effect on misclassifying “Normal” as “Abnormal” since postponement of newborn screening to a later age causes the quantization error to boost drastically, hence, easily exceeding the value of the first decision threshold.
Keywords: self-organizing kohonen maps (SOM), classification algorithm, outlier detection, newborn screening for congenital hypothyroidism
Download this article:
Year: 2013 Vol.: 62 No.: 2
Record ID: 42 [ Page 6 of 8, No. 19 ]
Career opportunities in the pharmaceutical industry
Authors: Jennifer Ly
Abstract:
Keywords:
Download this article:
Year: 2013 Vol.: 62 No.: 1
Record ID: 41 [ Page 6 of 8, No. 20 ]
An elementary proof of independence of least squares estimation of regression coefficients and of variance in linear regression
Authors: Alexaander R. De Leon; Joyce Raymund B. Punzalan
Abstract:
Keywords:
Download this article:
Year: 2013 Vol.: 62 No.: 1