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Record ID: 30 [ Page 14 of 16, No. 1 ]
Analysis of Mother's Day Celebration Via Circular Statistics
Authors: Ali H. Abuzaid
Abstract:
This paper handles with much emphasis mother's day celebration around the world a day that is celebrated on various days in different countries. These days are marked in relation to certain historical, religious or mythical events for every nation. The celebration of mother's day by 152 nations is analyzed using a set of circular statistics procedures to study its characteristics. The frequencies of celebration days are modeled, possible clusters and outliers are defined to assess possible factors that may affect the celebration in a certain date. These factors are found to be culture, language, colonization and neighborhood with insignificant role of religion.
Keywords: boxplot; cluster; direction; outlier
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Year: 2012 Vol.: 61 No.: 2
Record ID: 29 [ Page 14 of 16, No. 2 ]
Purposive Sampling as an Optimal Bayes Sampling Design
Authors: Jacqueline M. Guarte
Abstract:
Purposive sampling takes place when the researcher’s knowledge about the population is used to handpick the units to be included in the sample. This is hinged on the experienced researcher’s belief that the handpicked sampling units will provide “enough” information to characterize the population. Bayesian analysis makes explicit use of prior information as part of the model to satisfy some optimality criteria. Hence, purposive rather than purely random locations of design points need to be chosen. This paper presents a proof that purposive sampling is an optimal Bayes sampling design. Purposive sampling satisfies the sufficient condition for an optimal Bayes sampling design set by Zacks (1969) for single-phase designs. It is shown that the posterior Bayes risk of the population parameter ? given the sample observations is independent of the observed values under purposive sampling. The parameter of interest is the population mean. The normal distribution is used for the sampling distribution and the prior distribution of the population mean due to its universal significance and mathematical maneuverability. The squared error loss function is used in determining the posterior Bayes risk associated with estimating the population mean, with the sample mean as estimator. The posterior Bayes risk under simple random sampling is also determined for comparison purposes. It is shown that the risk levels under purposive sampling are lower than those under simple random sampling when important model parameters are made to vary.
Keywords: purposive sampling; optimal Bayes sampling design; posterior Bayes risk
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Year: 2012 Vol.: 61 No.: 2
Record ID: 28 [ Page 14 of 16, No. 3 ]
Small Area Estimation with a Multivariate Spatial-Temporal Model
Authors: Arturo M. Martinez, Jr
Abstract:
A multivariate generalization of a spatial-temporal is postulated and used in model-based small area estimation where small area information is borrowed from other units through spatial and temporal correlations. An estimation procedure that combined the backfitting algorithm, AR-sieve bootstrap and Lorenz curve parameterization is proposed. The procedure is illustrated using data on mean per capita income quintiles of households in the Philippines with provincial unit of analysis. The generation of unit-record synthetic household income is feasible even if modeling is done at the provincial level. Estimates of poverty indices based on the synthetic unit-record data generated from the multivariate spatial-temporal model are more reliable than the direct survey estimates. There are only small deviations between the model-based and direct survey estimates of poverty indices at the domain level that validates the accuracy of the model-based small area estimates generated from the multivariate spatial-temporal model.
Keywords: backfitting algorithm; AR-sieve bootstrap; Lorenz curve parameterization; poverty index
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Year: 2012 Vol.: 61 No.: 2
Record ID: 26 [ Page 14 of 16, No. 4 ]
On the Misuse of Slovin's Formula
Authors: Jeffry J. Tejada; Joyce Raymond B. Punzalan
Abstract:
In a number of research studies involving surveys, the so-called Slovin's formula is used to determine the sample size. Unfortunately, many of these studies use the formula inappropriately, giving the wrong impression that it can be used in just about any sampling problem. This paper provides a careful examination of the formula, showing that it is applicable only when estimating a population proportion and when the confidence coefficient is 95%. Moreover, it is optimal only when the unknown population proportion is believed to be close to 0.5.
Keywords: Slovin�s formula; sample size; margin of error
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Year: 2012 Vol.: 61 No.: 1
Record ID: 25 [ Page 14 of 16, No. 5 ]
Ranked Set Sampling
Authors: Kevin Carl P. Santos
Abstract:
Keywords:
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Year: 2012 Vol.: 61 No.: 1
Record ID: 24 [ Page 14 of 16, No. 6 ]
A Multivariate Probit Analysis on the Factors Influencing the Adoption of Water Saving Technologies by Rice Farmers in Sto. Domingo, Nueva Ecija
Authors: Daniel R. Raguindin; Eiffel A. De Vera
Abstract:
We study the adoption of rice farmers of some water saving technologies (WST) such as controlled irrigation, direct seeding, land leveling and aerobic rice system. A multivariate probit model for the adoption of each WST is constructed since usage of different technologies exhibit correlation. The significant factors that influence the WST adoption are education, experience in rice farming, family income of the farmers, and size of manpower involved in farming. Higher education is needed to enhance the ability to successfully implement the WST. Experience in rice farming, i.e., the number of years a farmer is involved in rice management and production, increases the likelihood of adoption among farmers. Farmers with high income have lower likelihood of adoption since the production system in place is already efficient. Furthermore, a farmer is more likely to adopt the technology as more manpower is involved in the production system. The estimated model indicated that the probability of adoption of controlled irrigation is higher than the other three WST. In addition, the adopters of WST had greater output in terms of the harvested rice.
Keywords: water saving technology; multivariate probit model; univariate probit model
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Year: 2012 Vol.: 61 No.: 1
Record ID: 23 [ Page 14 of 16, No. 7 ]
Sampling with Probability Proportional to Aggregate Size Using Nonparametric Bootstrap in Estimating Total Production Area of Top Cereals and Root Crops Across Philippine Regions
Authors: Maria Sofia A. Poblador; Iris Ivy M. Gauran
Abstract:
Cereal and root crop production are of primary interest to the country’s agricultural industry. The need to obtain reliable estimates of total area of production is therefore crucial. This paper examines the Sampling with Probability Proportional to Aggregate Size (PPAS) in terms of unbiasedness and precision of estimates as compared to two known sampling designs, Simple Random Sampling without Replacement (SRSWOR) and Sampling with Probability Proportional to Size Without Replacement (PPSWOR). Among several crops included in the 2002 Philippine Census of Agriculture, rice and corn are considered for cereals, while cassava and sweet potato for root crops. Crop area, which is believed to be highly correlated with total production area, is utilized as auxiliary information. Estimates of total production area are obtained under 1%, 5% and 10% sampling rates. To be able to evaluate precision of PPAS estimates, nonparametric bootstrap variance estimation is performed. It was found out that PPAS estimates are generally better than the two other sampling designs when it comes to precision but almost at par when it comes to unbiasedness.
Keywords: probability proportional to aggregate size sampling; probability proportional to size sampling; simple random sampling; nonparametric bootstrap estimation
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Year: 2012 Vol.: 61 No.: 1
Record ID: 22 [ Page 14 of 16, No. 8 ]
Econometric Modeling of Panel Data on the Saving Patterns of Philippine Agricultural Households
Authors: Angelo M. Alberto; Lisa Grace S. Bersales
Abstract:
This study aims to identify significant determinants of Philippine agricultural household saving using aggregate (regional) household panel data from the Family Income and Expenditure Survey (FIES) (1991 to 2006). Two definitions of saving are used - with and without expenses on durable goods as expenditure item. Guided by analyses using fixed effects models for panel data, the study identifies age of household head, self-employment of household head, land distribution, and young dependency rate as significant determinants of agricultural household saving. Self-employment, however, is significant only when expenses on durable goods is considered as an expenditure item. Also, time and cross-section fixed effects suggest that there are certain years and regions which had less agricultural household saving.
Keywords: panel data; fixed effects; saving rate; agricultural household
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Year: 2012 Vol.: 61 No.: 1
Record ID: 21 [ Page 14 of 16, No. 9 ]
Classification of Congenital Hypothyroidism in Newborn Screening Using Self-Organizing Maps
Authors: Iris Ivy M. Gauran; Maria Sofia Criselda A. Poblador
Abstract:
Each day, 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 widely known as a tool for visualization and clustering, the researchers want to probe on its ability as a tool for classification, particularly in detecting outliers. Results show that a lower misclassification rate yields from a self-organizing map with higher learning rate and larger training sample size. A bootstrap estimate of the variability of the misclassification error of roughly around 5% is also obtained. The misclassification error rate is lower when the original validation sample is used, compared to the average misclassification error rate computed from the bootstrap validation samples. Particularly, for a learning rate of 0.8 and a ratio of 2:1 training to validation sample, a 2.04% misclassification against 7.93% misclassification with 4.86% standard deviation is observed.
Keywords: self-organizing kohonen maps (SOM); classification algorithm; outlier detection; newborn screening for congenital hypothyroidism
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Year: 2012 Vol.: 61 No.: 1
Record ID: 20 [ Page 14 of 16, No. 10 ]
In a number of research studies involving surveys, the so-called Slovin's formula is used to determine the sample size. Unfortunately, many of these studies use the formula inappropriately, giving the wrong impression that it can be used in just about an
Authors: Lara Paul D. Abitona; Zita VJ Albacea
Abstract:
This paper aims to present methodologies in estimating the number of Vitamin A defi cient children aged six months to fi ve years in the Philippine provinces. Data from the 6th National Nutrition Survey (NNS), specifi cally, the data on plasma retinol which is used to directly determine Vitamin A defi ciency is used to compare direct and model-based methods. The direct estimates obtained was used as the dependent variable while the 2000 Census of Population and Housing and 2002 Field Health Service Information System were used as sources of auxiliary variables in the Poisson regression fi tted using robust standard errors which resulted to a model with Pseudo-R2 of 55.57%. Measures of precision and reliability were also obtained to assess the properties of the estimates for the provincial estimates. In direct estimation technique, 71 provinces have valid estimates but the coeffi cient of variations are all greater than 20%. On the other hand, valid model-based estimates using Poisson regression were observed for 72 provinces, but the coeffi cient of variations are at most 10% for 78% of these provinces. The use of Poisson regression based model generated more precise estimates of the number of children with Vitamin A defi ciency for the provinces.
Keywords: Small area estimation; Poisson regression model
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Year: 2012 Vol.: 61 No.: 1