Sex: Male
Education:
- Doctor of Philosophy in Statistics, University of the Philippines Diliman, 2017
- Master of Science in Statistics, University of the Philippines Diliman, 2011
- Bachelor of Science in Statistics, University of the Philippines Diliman, 2009
Field of Specialization
Statistical modelling
Regression analysis
Applied statistics
Statistical analysis
Researches:
Article title: Adjusting Person Fit Index for Skewness in Cognitive Diagnosis Modeling
Authors: Kevin Carl Santos, Jimmy de la Torre, Matthias Von Davier
Publication title: Journal of Classification 37(2), July 2019
Abstract:
Because the validity of diagnostic information generated by cognitive diagnosis models (CDMs) depends on the appropriateness of the estimated attribute profiles, it is imperative to ensure the accurate measurement of students’ test performance by conducting person fit (PF) evaluation to avoid flawed remediation measures. The standardized log-likelihood statistic lZ has been extended to the CDM framework. However, its null distribution is found to be negatively skewed. To address this issue, this study applies different methods of adjusting the skewness of lZ that have been proposed in the item response theory context, namely, χ²-approximation, Cornish-Fisher expansion, and Edgeworth expansion to bring its null distribution closer to the standard normal distribution. The skewness-corrected PF statistics are investigated by calculating their type I error and detection rates using a simulation study. Fraction-subtraction data are also used to illustrate the application of these PF statistics.
Full text available upon request to the author
Article title: Improving Predictive Accuracy of Logistic Regression Model Using Ranked Set Samples
Authors: Kevin Carl Santos and Erniel B. Barrios
Publication title: Communication in Statistics- Simulation and Computation 46(1), February 2015
Abstract:
Logistic regression is often confronted with separation of likelihood problem, especially with unbalanced success-failure distribution. We propose to address this issue by drawing a ranked set sample (RSS). Simulation studies illustrated the advantages of logistic regression models fitted with RSS samples with small sample size regardless of the distribution of the binary response. As sample size increases, RSS eventually becomes comparable to RSS, but still has the advantage over RSS in mitigating the problem of separation of likelihood. Even in the presence of ranking errors, models from RSS samples yields higher predictive ability than its SRS counterpart.
Full text available upon request to the author
Article title: Management and Malignancy Rate of Thyroid Nodules with a Cytologic Diagnosis of Atypia or Follicular Lesion of Undetermined Significance
Authors: Armi Dianne Carlos, Roberto Mirasol, Eduardo Thomas Aquino, Maria Lourdes Goco, et al.
Publication title: Journal of the ASEAN Federation of Endocrine Societies 29(1):78-84, May 2014
Abstract:
This study describes the clinical data of adult patients who underwent Fine Needle Aspiration Biopsy (FNAB) of thyroid nodule(s) with a cytologic diagnosis of Atypia or Follicular Lesion of Undetermined Significance (AUS or FLUS) at St. Luke's Medical Center from January 2012 to October 2013. Methodology. Adult patients who underwent FNAB of the thyroid nodule with a cytologic diagnosis of AUS or FLUS were studied retrospectively using the ultrasound result, initial consultation form and operative techniques of these patients. The cytologic and histopathologic diagnoses were retrieved through the electronic Healthcare-Results Management System. Results and Conclusion. A third (34%) of the patients with a cytologic diagnosis of AUS or FLUS (8.9%) underwent surgery. Of the 68 patients who underwent surgery, 44 were benign and 24 were malignant with a malignancy rate of 35.3%. Preoperatively, there were no ultrasound characteristics or microscopic descriptions significantly associated with malignancy. The recommendation of the Bethesda System to do a repeat FNAB in these thyroid nodules should, therefore, be reconsidered.
Full text link: https://tinyurl.com/yt86bhmb
Article title: Correlation of total IgE, house-dust mite specific IgE and absolute eosinophils in an asthmatic pediatric population
Authors: Maricar W. Ching, Jennifer Maries G. Yap, Kevin Carl P. Santos, Cesar M. Ong, and John Donnie A. Ramos
Publication title: Philippine Science Letters 6(2), 2013
Abstract:
No available
Full text link: https://tinyurl.com/nu87ywfu
Article title: Investigating the Efficiency of Stratified Ranked Set Sampling using Nonparametric Bootstrap Estimation Approach
Authors: Kevin Carl P. Santos and Jenniebie Salagubang
Publication title: The Philippine Statistician 60, 2011
Abstract:
This paper aims to compare stratified random sampling and stratified ranked set sampling. A simulation study is conducted to evaluate the performance of the parameter estimates on both sampling techniques. Population sizes, sampling rates, stratum sizes, and correlation of the target variable and concomitant variable were varied, nonparametric bootstrap was then used in estimating the mean and its standard error. The coefficient of variation (CV) and the bias of the bootstrap estimates were compared. Stratified ranked set sampling generally outperforms stratified random sampling in terms of bias most especially for small populations. The two sampling designs were used in estimating the average mango production per barangay in the country.
Full text link: https://tinyurl.com/69hpxsys
Article title: Nonparametric Bootstrap Estimation of the Population Ratio using Ranked Set Sampling
Authors: Kevin Carl P. Santos, Charisse Mae I. Castillo, Reyna Belle d.S. de Jesus, Nina B. Telan, Crystal Angela P. Vidal
Publication title: The Philippine Statistician 61(2):53-66, 2012
Abstract:
Ranked Set Sampling (RSS) yields unbiased and more reliable estimators of the population mean and proportion while keeping low costs. Using nonparametric bootstrap estimation, the efficiency of the ratio estimates using RSS with Simple Random Sampling (SRS) are compared. A simulation study accounting for the sampling rate, population size, population variance and correlation with the concomitant variable was conducted to compare RSS and SRS in estimating ratios. When ranking was done on the numerator characteristic, RSS generally performs better than SRS in terms of their relative bias. Likewise, in terms of precision, RSS generally produces better estimates when ranking was done on the numerator characteristic. On homogeneous populations, contrary to what was expected, RSS performed better over SRS. On heterogeneous populations, on the other hand, the two sampling designs are generally comparable
Full text link: https://tinyurl.com/4aa4x6r9