| No. of records per page: 10 | 20 | 30 | 50 | 100 | Show all |
Record ID: 80 [ Page 9 of 16, No. 1 ]
Purposive Sampling in the Analysis of Count Data
Authors: Paolo Victor T. Redondo
Abstract:
Purposive sampling is a non-probability sampling method which is oftentimes used whenever random/probability sampling is not efficient, too costly (either in finance or time) and not feasible. Also, most of the data collected for studies in the present time exhibit the property of count and thus, analysis of such data needs the appropriate tool; commonly the Poisson Regression. The goal of this study is to determine whether the relative location-based purposive sampling can improve the estimates produced by the Poisson regression and if the proposed sampling procedure can reduce the required sample size to have a more efficient and good quality results simultaneously. Simulation of different scenarios are done and several possible partitions (based on relative location) from where the sample will come from are considered. Some partitions are deemed to work better even for small sample size, say 50, while others work as good as their respective simple random sample counterparts.
Keywords: purposive sampling, poisson regression, sample size
Download this article:
Year: 2016 Vol.: 65 No.: 1
Record ID: 79 [ Page 9 of 16, No. 2 ]
AR-Sieve-based Prediction Interval for Sustainable Development Index
Authors: Jachelle Anne Dimapilis
Abstract:
We propose a procedure for monitoring progress of sustainable development measured by indices. AR-sieve-based nonparametric prediction interval is constructed to determine whether the movement of the indices is significant or not. Points outside the interval are considered significant and imply positive or negative movement of the indices. This method is used in the construction of prediction interval for sustainable development index for the Philippine. The interval is indeed capable of detecting significant movements that can be explained by policies and other factors.
Keywords: sustainable development index, AR-sieve bootstrap, nonparametric prediction interval
Download this article:
Year: 2016 Vol.: 65 No.: 1
Record ID: 78 [ Page 9 of 16, No. 3 ]
Value-at-Risk Estimates from a SETAR Model
Authors: Joselito C. Magadia
Abstract:
A self-exciting threshold autoregressive (SETAR) model will be fitted to PSEi and value-at-risk estimates would be computed. Backtesting procedures would be employed to assess the accuracy of the estimates and compared with estimates derived from two other approaches to VaR estimation.
Keywords: threshold models, backtesting, APARCH
Download this article:
Year: 2016 Vol.: 65 No.: 1
Record ID: 77 [ Page 9 of 16, No. 4 ]
Comparison of Ordinal Logistic Regression with Tree-Based Methods in Predicting Socioeconomic Classes in the Philippines
Authors: Michael Daniel C. Lucagbo
Abstract:
The task of classifying Philippine households according to their socioeconomic class (SEC) has been tackled anew in a collaborative work between the Marketing and Opinion Research Society of the Philippines (MORES), the former National Statistics Office (NSO) and the University of the Philippines School of Statistics. This new system of classifying Philippine households has been introduced in the 12th National Convention on Statistics, in a paper entitled 1SEC 2012: The New Philippine Socioeconomic Classification. To predict the SEC of a household, certain household characteristics are used as predictors. The 1SEC Instrument, whose scoring system is based on the ordinal logistic regression model, is then used to predict the household’s SEC. Recently, the statistical literature has seen the development of novel tree-based learning algorithms. This paper shows that the ordinal logistic regression model can still classify households better than three popular tree-based statistical learning methods: bootstrap aggregation (or bagging), random forests, and boosting. In addition, this paper identifies which clusters are easier to predict than others.
Keywords: socioeconomic classification, ordinal logistic regression, bagging, random forests, boosting
Download this article:
Year: 2016 Vol.: 65 No.: 1
Record ID: 76 [ Page 9 of 16, No. 5 ]
The Recursive Alpha (RAlph) Coefficients: Quantifying Inter-Item Cohesion under Indirect Range Restriction
Authors: Michael Van B. Supranes; John Francis J. Guntan; Joy Pauline Adrienne C. Padua; Joseph Ryan G. Lansangan
Abstract:
Range restriction is a known cause of underestimation in the Cronbach’s Alpha reliability coefficient. The estimate of the Cronbach’s Alpha is usually adjusted to minimize bias, but existing methods require information about the population. In the case of indirect range restriction however, such information may not be readily or intuitively available. A data-driven bootstrap-based estimator that requires minimal assumptions about the unrestricted population, called the Recursive Alpha (RAlph) coefficient, is therefore proposed. Based on the simulation studies, the two versions of the Ralph coefficient perform best when the information associated to the range restriction is strongly correlated with the characteristic being measured, and when the true reliability coefficient Alpha is high. Also, the RAlph coefficients are found to be effective in minimizing the error in estimating Alpha under strong presence of range restriction. Moreover, considerations on the length of the instrument, scale of the responses, and sample size aid in minimizing the error of the proposed coefficients. In support of the simulation results, an empirical study using behavioral data on social media users is carried out, and evidently, the RAlph coefficients are far better than the ordinary Cronbach’s Alpha estimate.
Keywords: Range Restriction, Adjusted Cronbach’s Alpha, Bootstrap Sampling
Download this article:
Year: 2015 Vol.: 64 No.: 2
Record ID: 75 [ Page 9 of 16, No. 6 ]
Incidence of Crimes and Effectiveness of Interventions in the National Capital Region: Evidence from Panel Data
Authors: Michael Daniel C. Lucagbo; Lianne S. De La Cruz; Jecca V. Narvasa; Micah Jane A. Paglicawan
Abstract:
Efforts to bring down the incidence of crimes have been intensified by the Philippine National Police (PNP). The index crimes are prioritized among these crimes. These crimes include theft, robbery, carnapping, and motornapping. Interventions to bring down the incidence of crimes have recently been enacted by the National Capital Region Police Office (NCRPO) of the PNP. These interventions include increases in number of police personnel, mobile patrols, beat patrols, and checkpoints. In this study, the effect of each of these interventions is examined in a panel data analysis using weekly data gathered from all of the police stations in NCR. This paper performs a district-level analysis of the crimes and interventions. The negative binomial regression model for panel data is used to quantify the effects of the interventions on the incidence of index crimes. Results show that some (but not all) of these interventions are effective in reducing crime. The results also show differences in the effects of the interventions across for the different districts. Resources should thus be redirected towards these effective strategies. The differences in the effects of the interventions among the different crimes are also studied.
Keywords: index crimes, intervention, panel data, negative binomial regression
Download this article:
Year: 2015 Vol.: 64 No.: 2
Record ID: 74 [ Page 9 of 16, No. 7 ]
Bootstrapping Penalty Analysis in Sensory Evaluation of Pizza Products
Authors: Catherine Estiaga
Abstract:
Penalty analysis is a popular method used to evaluate data from sensory evaluation using the Just About Right Scale and the Hedonic Scale. Although the test estimates the mean drops for the “Too Little” and “Too Much” categories of product attributes, penalty analysis does not provide information that can be used to test the effect of each attribute on the overall liking score. Bootstrap resampling method when used together with penalty analysis estimates the standard error of the mean drops and allows to test for the significance. This method is used in product testing of pizza products.
Keywords: bootstrap method, penalty analysis, just about right scale, hedonic scale, mean drops
Download this article:
Year: 2015 Vol.: 64 No.: 2
Record ID: 73 [ Page 9 of 16, No. 8 ]
Statistical Evaluation of In Vivo Micronucleus Assays in Toxicology
Authors: John Closter F. Olivo
Abstract:
Several alternative statistical procedures have been suggested and published to statistically analyze the incidence of micronucleated polychromatic erythrocytes (MNPCs) among treatment groups, but no standard procedure has been singled out and exclusively recommended. In this study, the potential of TO2 to induce chromosomal damage is tested using both Poisson and quasi-Poisson models for the statistical evaluation of in vivo micronucleus (MN) assay. The genotoxic activity of T02 is assessed in the rodent bone marrow micronucleus test using male mice. Results show that MN frequencies are significantly elevated in mice exposed to any dose level of T02 administered orally in a single frequency of dose. Moreover, results indicate that T02 is tested to be a positive compound under the anticipated condition of the tests used.
Keywords: in vivo; micronucleus, MNPC; Poisson model; quasi-Poisson model; TO2
Download this article:
Year: 2015 Vol.: 64 No.: 2
Record ID: 72 [ Page 9 of 16, No. 9 ]
Modelling Rice Yield in the Philippines Using Dynamic Spatio-Temporal Models
Authors: Stephen Jun V. Villejo
Abstract:
Recent unpredictable and extreme weather episodes and infestation are some of the realistic occurrences of structural change in the agricultural system which produce outliers and extreme values in our data, and consequently pose problems when building statistical models. An estimation procedure which is robust to structural change is therefore necessary. Three spatial-temporal models with varying dynamic characteristics of the parameters are postulated each with a different estimation procedure for the agricultural yield in irrigated areas of the Philippines. One of which is a robust estimation procedure using forward search algorithm with bootstrap in a backfitting algorithm. The other two algorithms also used the backfitting algorithm but infused with the Cochranne-Orcutt procedure. The robust estimation procedure and the other one which considers varying parameter across space gave competitive predictive abilities and are better than the ordinary linear model. Simulation studies show the superiority of the robust estimation procedure over the Cochranne-Orcutt procedure and ordinary linear model in the presence of structural change.
Keywords: Spatial-temporal model; Backfitting algorithm; robust estimation; additive model
Download this article:
Year: 2015 Vol.: 64 No.: 2
Record ID: 71 [ Page 9 of 16, No. 10 ]
Some Zero Inflated Poisson-Based Combined Exponentially Weighted Moving Average Control Charts for Disease Surveillance
Authors: Robert Neil F. Leong; Frumencio F. Co; Daniel Stanley Y. Tan
Abstract:
One of the main areas of public health surveillance is infectious disease surveillance. With infectious disease backgrounds usually being more complex, appropriate surveillance schemes must be in order. One such procedure is through the use of control charts. However, with most background processes following a zero-inflated Poisson (ZIP) distribution as brought about by the extra variability due to excess zeros, the control charting procedures must be properly developed to address this issue. Hence in this paper, drawing inspiration from the development of combined control charting procedures for simultaneously monitoring each ZIP parameter individually in the context of statistical process control (SPC), several combined exponentially weighted moving average (EWMA) control charting procedures were proposed (Bernoulli-ZIP and CRL-ZTP EWMA charts). Through an extensive simulation study involving multiple parameter settings and outbreak model considerations (i.e., different shapes, magnitude, and duration), some key results were observed. These include the applicability of performing combined control charting procedures for disease surveillance with a ZIP background using EWMA techniques. For demonstration purposes, application with an actual data, using confirmed measles cases in the National Capital Region (NCR) from Jan. 1, 2010 to Jan. 14, 2015, revealed the comparability of the Bernoulli-ZIP EWMA scheme to historical limits method currently in use.
Keywords: EWMA control charts, disease surveillance, ZIP distribution, measles
Download this article:
Year: 2015 Vol.: 64 No.: 2