Statistical Sum Research Articles

Home-Based Connected Devices Combined With Statistical Process Control for the Early Detection of Respiratory Exacerbations by Patients With Cystic Fibrosis: Pilot Interventional Study With a Pre-Post Design.

Currently, patients with cystic fibrosis do not routinely monitor their respiratory function at home. This study aims to assess the clinical validity of using different connected health devices at home to measure 5 physiological parameters to help prevent exacerbations on a personalized basis from the perspective of patient empowerment. A multicenter interventional pilot study including 36 patients was conducted. Statistical process control-the cumulative sum control chart (CUSUM)-was used with connected health device measures with the objective of sending patients alerts at a relevant time in order to identify their individual risk of exacerbations. Associated patient education was delivered. Quantitative and qualitative data were collected. One-half (18/36) of the patients completed the protocol through the end of the study. During the 12-month intervention, 6162 measures were collected with connected health devices, 387 alerts were sent, and 33 exacerbations were reported. The precision of alerts to detect exacerbations was weak for all parameters, which may be partly related to the low compliance of patients with the measurements. However, a decrease in the median number of exacerbations from 12 months before the study to after the 12-month intervention was observed for patients. The use of connected health devices associated with statistical process control showed that it was not acceptable for all patients, especially because of the burden related to measurements. However, the results suggest that it may be promising, after adaptations, for early identification and better management of exacerbations. ClinicalTrials.gov NCT03304028; https://clinicaltrials.gov/study/NCT03304028.

On Statistical Riemann-Stieltjes Integrablility and Deferred Cesàro Summabilit

In this paper, we first introduce and study the notion of statistical Riemann-Stieltjes sum for the sequence of functions and establish some elementary results based on this notion. Subsequently, we extend this notion to the probability space and demonstrate some new results for sequence of distribution functions. Furthermore, we suggest the deferred Cesàro summability method for Riemann-Stieltjes sum. We then establish various inclusion theorems based on our proposed methods in association with the Riemann-Stieltjes sum for the sequence of usual functions as well as distribution functions in Rn.

High-dimensional causal mediation analysis by partial sum statistic and sample splitting strategy in imaging genetics application.

Causal mediation analysis provides a systematic approach to explore the causal role of one or more mediators in the association between exposure and outcome. In omics or imaging data analysis, mediators are often high-dimensional, which brings new statistical challenges. Existing methods either violate causal assumptions or fail in interpretable variable selection. Additionally, mediators are often highly correlated, presenting difficulties in selecting and prioritizing top mediators. To address these issues, we develop a framework using Partial Sum Statistic and Sample Splitting Strategy, namely PS5, for high-dimensional causal mediation analysis. The method provides a powerful global mediation test satisfying causal assumptions, followed by an algorithm to select and prioritize active mediators with quantification of individual mediation contributions. We demonstrate its accurate type I error control, superior statistical power, reduced bias in mediation effect estimation, and accurate mediator selection using extensive simulations of varying levels of effect size, signal sparsity, and mediator correlations. Finally, we apply PS5 to an imaging genetics dataset of chronic obstructive pulmonary disease (COPD) patients ( N =8,897) in the COPDGene study to examine the causal mediation role of lung images ( p =5,810) in the associations between polygenic risk score and lung function and between smoking exposure and lung function, respectively. Both causal mediation analyses successfully estimate the global indirect effect and detect mediating image regions. Collectively, we find a region in the lower lobe of the right lung with a strong and concordant mediation effect for both genetic and environmental exposures. This suggests that targeted treatment toward this region might mitigate the severity of COPD due to genetic and smoking effects.

A doubly robust estimator for the Mann Whitney Wilcoxon rank sum test when applied for causal inference in observational studies

ABSTRACT The Mann–Whitney–Wilcoxon rank sum test (MWWRST) is a widely used method for comparing two treatment groups in randomized control trials, particularly when dealing with highly skewed data. However, when applied to observational study data, the MWWRST often yields invalid results for causal inference. To address this limitation, Wu et al. (Causal inference for Mann–Whitney–Wilcoxon rank sum and other nonparametric statistics, Stat. Med. 33 (2014), pp. 1261–1271) introduced an approach that incorporates inverse probability weighting (IPW) into this rank-based statistic to mitigate confounding effects. Subsequently, Mao (On causal estimation using U-statistics, Biometrika 105 (2018), pp. 215–220), Zhang et al. (Estimating Mann Whitney-type causal effects, J. Causal Inference 7 (2019), ARTICLE ID 20180010), and Ai et al. (A Mann–Whitney test of distributional effects in a multivalued treatment, J. Stat. Plan. Inference 209 (2020), pp. 85–100) extended this IPW estimator to develop doubly robust estimators. Nevertheless, each of these approaches has notable limitations. Mao's method imposes stringent assumptions that may not align with real-world study data. Zhang et al.'s (Estimating Mann Whitney-type causal effects, J. Causal Inference 7 (2019), ARTICLE ID 20180010) estimators rely on bootstrap inference, which suffers from computational inefficiency and lacks known asymptotic properties. Meanwhile, Ai et al. (A Mann–Whitney test of distributional effects in a multivalued treatment, J. Stat. Plan. Inference 209 (2020), pp. 85–100) primarily focus on testing the null hypothesis of equal distributions between two groups, which is a more stringent assumption that may not be well-suited to the primary practical application of MWWRST. In this paper, we aim to address these limitations by leveraging functional response models (FRM) to develop doubly robust estimators. We demonstrate the performance of our proposed approach using both simulated and real study data.

Sequential monitoring for conditional quantiles of general conditional heteroscedastic time series models

AbstractIn this study, we introduce an online monitoring procedure designed to sequentially detect change points in the conditional quantiles of location‐scale time series models. This statistical process control issue holds great significance in risk management, particularly in measuring the value‐at‐risk or expected shortfall of financial assets. Our approach employs suitable detectors, including cumulative sum statistics. We then define a stopping rule and determine control limits based on asymptotic theorems to signal an anomaly. To further evaluate the proposed methods, we conduct a comprehensive empirical study analyzing various aspects of our monitoring procedures when applied to location‐scale time series models. Additionally, we perform a real data analysis using the daily returns of the Korea Composite Stock Price Index (KOSPI) and EuroStoxx 50 indices to affirm the adequacy of the proposed monitoring procedures in real‐world applications.

A preliminary study of optimal treatment response rates in patients undergoing hepatic arterial infusion chemotherapy combined with molecular targeting and immunotherapy.

This study aimed to examine the effectiveness of the best response rate (BRR) as a surrogate for overall survival (OS), using the modified Response Evaluation Criteria in Solid Tumors (mRECIST), in patients with unresectable hepatocellular carcinoma (HCC) undergoing hepatic arterial infusion chemotherapy (HAIC) with fluorouracil, leucovorin, and oxaliplatin (FOLFOX) combined with molecular targeting and immunotherapy. This study enrolled 111 consecutive patients who had complete imaging data. The median age of patients was 58 years (IQR 50.5-65.0). Among the patients, those with Barcelona Clinic Liver Cancer (BCLC) stage A, BCLC stage B, and BCLC stage C comprised 6.4%, 19.1%, and 73.6%, respectively. The optimal threshold of BRR can be determined using restricted cubic splines (RCS) and the rank sum statistics of maximum selection. Survival curves of patients in the high rating and low rating groups were plotted. We then used the change-in-estimate (CIE) method to filter out confounders and the inverse probability of treatment weighting (IPTW) to balance confounders between the two groups to assess the robustness of the results. The median frequency of the combination treatment regimens administered in the overall population was 3 times (IQR 2.0-3.0). The optimal BRR truncation value calculated was -0.2. Based on this value, 77 patients were categorized as the low rating group and 34 as the high rating group. The differences in the OS between the high and low rating groups were statistically significant (7 months [95%CI 6.0-14.0] vs. 30 months [95%CI 30.0-]; p< 0.001). Using the absolute 10% cut-off value, the CIE method was used to screen out the following confounding factors affecting prognosis: successful conversion surgery, baseline tumor size, BCLC stage, serum total bilirubin level, number of interventional treatments, alpha-fetoprotein level, presence of inferior vena cava tumor thrombus, and partial thrombin activation time. The survival curve was then plotted again using IPTW for confounding factors, and it was found that the low rating group continued to have better OS than the high rating group. Finally, the relationship between BRR and baseline factors was analyzed, and inferior vena cava tumor thrombus and baseline tumor size correlated significantly with BRR. BRR can be used as a surrogate endpoint for OS in unresectable HCC patients undergoing FOLFOX-HAIC in combination with molecular targeting and immunotherapy. Thus, by calculating the BRR, the prognosis of HCC patients after combination therapy can be predicted. Inferior vena cava tumor thrombus and baseline tumor size were closely associated with the BRR.

Fitting copulas in the case of missing data

In this paper we deal with parametric estimation of the copula in the case of missing data. The data items with the same pattern of complete and missing data are combined into a subset. This approach corresponds to the MCAR model for missing data. We construct a specific Cramér–von Mises statistic as a sum of such statistics for the several missing data patterns. The minimization of the statistic gives the estimators for the parameters. We prove asymptotic normality of the parameter estimators and of the Cramér–von Mises statistic.

Cost-effectiveness of screening for chronic kidney disease using a cumulative eGFR-based statistic.

Routine screening for chronic kidney disease (CKD) could enable timely interventions to slow down disease progression, but currently there are no clinical guidelines for screening. We aim to evaluate the cost-effectiveness of screening for CKD using a novel analytical tool based on a cumulative sum statistic of estimated glomerular filtration rate (CUSUMGFR). We developed a microsimulation model that captured CKD disease progression, major complications, patients' awareness, and treatment adherence for a nationally representative synthetic cohort of age ≥ 30 years in the United States. In addition to the status quo with no screening, we considered four CUSUMGFR-based universal screening policies by frequency (annual or biennial) and starting age (30 or 60 years), and two targeted annual screening policies for patients with hypertension and diabetes, respectively. For each policy, we evaluated the total discounted disability-adjusted life years (DALYs) and direct health costs over a lifetime horizon and estimated the incremental cost-effectiveness ratio (ICER). We further performed one-way and probabilistic sensitivity analyses to assess the impact of parameter uncertainty. Compared with the status quo, all the CUSUMGFR-based screening policies were cost-effective under the willingness-to-pay (WTP) range of $50,000 -$100,000, with the estimated incremental cost-effectiveness ratios (ICERs) ranging from $15,614/DALYs averted to $54,373/DALYs averted. Universal annual screening with starting age of 30 was the non-dominated policy on the cost-effectiveness frontier under the WTP of approximately $25,000. Adding more recent treatment option of sodium-glucose cotransporter-2 (SGLT2) inhibitors to the treatment regimen was found to be cost-saving. Among the most influential model parameters, variation in the CKD progression rate, adherence, and testing cost resulted in the highest variability in model outcomes. CUSUMGFR-based screening policies for CKD are highly cost-effective in identifying patients at risk of end stage kidney disease in early stages of CKD. Given its simple requirement of a basic blood test, the CUSUMGFR-based screening can be easily incorporated into clinical workflow for disease monitoring and prevention.

Wilcoxon-Type Control Charts Based on Multiple Scans

In this article, we establish new distribution-free Shewhart-type control charts based on rank sum statistics with signaling multiple scans-type rules. More precisely, two Wilcoxon-type chart statistics are considered in order to formulate the decision rule of the proposed monitoring scheme. In order to enhance the performance of the new nonparametric control charts, multiple scans-type rules are activated, which make the proposed chart more sensitive in detecting possible shifts of the underlying distribution. The appraisal of the proposed monitoring scheme is accomplished with the aid of the corresponding run length distribution under both in- and out-of-control cases. Thereof, exact formulae for the variance of the run length distribution and the average run length (ARL) of the proposed monitoring schemes are derived. A numerical investigation is carried out and depicts that the proposed schemes acquire better performance towards their competitors.

E-values for k-Sample Tests with Exponential Families

AbstractWe develop and compare e-variables for testing whether k samples of data are drawn from the same distribution, the alternative being that they come from different elements of an exponential family. We consider the GRO (growth-rate optimal) e-variables for (1) a ‘small’ null inside the same exponential family, and (2) a ‘large’ nonparametric null, as well as (3) an e-variable arrived at by conditioning on the sum of the sufficient statistics. (2) and (3) are efficiently computable, and extend ideas from Turner et al. (2021) and Wald (1947) respectively from Bernoulli to general exponential families. We provide theoretical and simulation-based comparisons of these e-variables in terms of their logarithmic growth rate, and find that for small effects all four e-variables behave surprisingly similarly; for the Gaussian location and Poisson families, e-variables (1) and (3) coincide; for Bernoulli, (1) and (2) coincide; but in general, whether (2) or (3) grows faster under the alternative is family-dependent. We furthermore discuss algorithms for numerically approximating (1).

Development of Adolescents' perceptions of the nursing image scale and evaluation of its psychometric properties: A methodological study

Background and purposeIt is important to assess the perception of the nursing image among adolescents, the group closest to the career decision, to enhance their view of the nursing image. This study was conducted to develop the Adolescents' Perceptions of Nursing Image Scale (APNIS) and evaluate its psychometric properties. MethodThe study has a descriptive, cross-sectional, correlational, and methodological design. The study was conducted with 614 adolescents aged 12–18 years in Turkey between October 15, 2022, and December 15, 2022. The data were analyzed using the Kaiser-Meyer-Olkin coefficient, Barlett's test, factor analyses, Cronbach's alpha reliability coefficient, split-half analysis, item sum statistics, Hotelling's T2, and test-retest analysis. ResultsAs a result of the explanatory factor analysis, the items on the scale were collected under six sub-dimensions, and the scale explained 62.843% of the total variance. Confirmatory factor analysis showed that the model fit was adequate. The total internal consistency Cronbach alpha value of the scale is 0.90, and the sub-dimension Cronbach alpha values are between 0.70 and 0.90. The Spearman-Brown coefficient of the scale was 0.94, the Guttman-split-half coefficient was 0.94, Hotelling's T2 value was 373.829, F = 9.510, and p < 0.001. As a result of the Tukey summability analysis, F = 0.431 and p > 0.05, the scale was found to be summable. The test-retest result of the scale was r = 0.899. ConclusionThe 38-item APNIS is a valid and reliable tool that assesses adolescents' perceptions of the nursing image. Practice implicationsThe scale, including universal items about the nursing image, is easy and practical to use.

Exact extreme, order, and sum statistics in a class of strongly correlated systems.

Even though strongly correlated systems are abundant, only a few exceptional cases admit analytical solutions. In this paper we present a large class of solvable systems with strong correlations. We consider a set of N independent and identically distributed random variables {X_{1},X_{2},...,X_{N}} whose common distribution has a parameter Y (or a set of parameters) which itself is random with its own distribution. For a fixed value of this parameter Y, the X_{i} variables are independent and we call them conditionally independent and identically distributed. However, once integrated over the distribution of the parameter Y, the X_{i} variables get strongly correlated yet retain a solvable structure for various observables, such as for the sum and the extremes of X_{i}^{'}s. This provides a simple procedure to generate a class of solvable strongly correlated systems. We illustrate how this procedure works via three physical examples where N particles on a line perform independent (i) Brownian motions, (ii) ballistic motions with random initial velocities, and (iii) Lévy flights, but they get strongly correlated via simultaneous resetting to the origin. Our results are verified in numerical simulations. This procedure can be used to generate an endless variety of solvable strongly correlated systems.

Cross-disorder GWAS meta-analysis of endocannabinoid DNA variations in major depressive disorder, bipolar disorder, attention deficit hyperactivity disorder, autism spectrum disorder, and schizophrenia

The endocannabinoid system (ECS) is implicated in multiple mental disorders. In this study, we explored DNA variations in the ECS across major depressive disorder (MDD), bipolar disorder, attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and schizophrenia by performing a cross-disorder genome-wide association study (GWAS) meta-analysis. We obtained six datasets from the Psychiatric Genomics Consortium containing GWAS summary statistics from European cohorts (284,023 cases and 508,515 controls). Effective sample size weighted meta-analysis was performed for 2241 single nucleotide polymorphisms (SNPs) pertaining to gene bodies of 33 endocannabinoid genes using METAL, where an overall z-statistic is calculated for each marker based on a weighted sum of individual statistics. Heterogeneity was examined with I2 and X2 tests. MAGMA gene-based analysis was also performed. We identified nine SNPs significantly associated with a change in risk of having a mental disorder. The lead SNP was rs12805732 (Gene: Diacylglycerol Lipase Alpha; DAGLA). Four SNPs had substantial heterogeneity (I2>60 %). DAGLA had the strongest association with disease risk in gene-based analysis. Our findings suggest that the ECS may be a shared pathway in mental disorders. Future studies validating these findings would contribute to the identification of biomarkers of disease risk across multiple mental disorders.

Joint Statistics of Partial Sums of Ordered i.n.d. Gamma Random Variables

From the perspective of wireless communication, as communication systems become more complex, order statistics have gained increasing importance, particularly in evaluating the performance of advanced technologies in fading channels. However, existing analytical methods are often too complex for practical use. In this research paper, we introduce innovative statistical findings concerning the sum of ordered gamma-distributed random variables. We examine various channel scenarios where these variables are independent but not-identically distributed. To demonstrate the practical applicability of our results, we provide a comprehensive closed-form expression for the statistics of the signal-to-interference-plus-noise ratio in a multiuser scheduling system. We also present numerical examples to illustrate the effectiveness of our approach. To ensure the accuracy of our analysis, we validate our analytical results through Monte Carlo simulations.

On the Exact Sum PDF and CDF of α-μ Variates

The sum of random variables (RVs) appears extensively in wireless communications, at large, both conventional and advanced, and has been subject of longstanding research. The statistical characterization of the referred sum is crucial to determine the performance of such communications systems. Although efforts have been undertaken to unveil these sum statistics, e.g., probability density function (PDF) and cumulative distribution function (CDF), no general efficient nor manageable solutions capable of evaluating the exact sum PDF and CDF are available to date. The only formulations are given in terms of either the multi-fold Brennan’s integral or the multivariate Fox <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</i> -function. Unfortunately, these methods are only feasible up to a certain number of RVs, meaning that when the number of RVs in the sum increases, the computation of the sum PDF and CDF is subject to stability problems, convergence issues, or inaccurate results. In this paper, we derive new, simple, exact formulations for the PDF and CDF of the sum of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</i> independent and identically distributed α-μ RVs. Unlike the available solutions, the computational complexity of our analytical expressions is independent of the number of summands. Capitalizing on our unprecedented findings, we analyze, in exact and asymptotic manners, the performance of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</i> -branch pre-detection equal-gain combining and maximal-ratio combining receivers over α-μ fading environments. The coding and diversity gains of the system for both receivers are analyzed and quantified. Moreover, numerical simulations show that the computation time reduces drastically when using our expressions, which are arguably the most efficient and manageable formulations derived so far.

Cluster Variation for Spatially Distributed Heterogeneous Systems

Fundamentals of cluster variation (CV) are developed for locally heterogeneous spatially distributed systems. The theory is based on the principles of homogeneous CV in which all variants of the location of the basis cluster on a heterogeneous lattice are additionally considered when it is translated over the system. The structure of the statistical sum of homogeneous CV is shown to remain upon moving to a heterogeneous or homogeneous spatially distributed lattice. However, cofactors of the statistical sum, which previously corresponded to homogeneous clusters, must now consider all arrangements of heterogeneous sites inside each cluster. The general approach is to use a layered structure of the transitional region with variable density between vapor and fluid on a planar square lattice. Explicit expressions for a heterogeneous statistical sum of the transitional region are given on the basis of a 3 × 3 cluster. Using a 2 × 2 cluster, it is shown how an explicit equation for the equilibrium particle distribution in the transitional region can be obtained from the heterogeneous statistical sum. A gradual increase in the size of the m × n basis cluster in the transitional region converges to the exact solution.

Cluster Variation for Spatially Distributed Heterogeneous Systems

Fundamentals of cluster variation (CV) are developed for locally heterogeneous spatially distributed systems. The theory is based on the principles of homogeneous CV in which all variants of the location of the basis cluster on a heterogeneous lattice are additionally considered when it is translated over the system. The structure of the statistical sum of homogeneous CV is shown to remain upon moving to a heterogeneous or homogeneous spatially distributed lattice. However, cofactors of the statistical sum, which previously corresponded to homogeneous clusters, must now consider all arrangements of heterogeneous sites inside each cluster. The general approach is to use a layered structure of the transitional region with variable density between vapor and fluid on a planar square lattice. Explicit expressions for a heterogeneous statistical sum of the transitional region are given on the basis of a 3 × 3 cluster. Using a 2 × 2 cluster, it is shown how an explicit equation for the equilibrium particle distribution in the transitional region can be obtained from the heterogeneous statistical sum. A gradual increase in the size of the m × n basis cluster in the transitional region converges to the exact solution.

Computationally efficient and data-adaptive changepoint inference in high dimension

Abstract High-dimensional changepoint inference that adapts to various change patterns has received much attention recently. We propose a simple, fast yet effective approach for adaptive changepoint testing. The key observation is that two statistics based on aggregating cumulative sum statistics over all dimensions and possible changepoints by taking their maximum and summation, respectively, are asymptotically independent under some mild conditions. Hence, we are able to form a new test by combining the p-values of the maximum- and summation-type statistics according to their asymptotic null distributions. To this end, we develop new tools and techniques to establish the asymptotic distribution of the maximum-type statistic under a more relaxed condition on componentwise correlations among all variables than those in existing literature. The proposed method is simple to use. It is adaptive to different levels of the sparsity of change signals, and is comparable to or even outperforms existing approaches as revealed by our numerical studies.

RESOURCES USED IN THE PROVISION OF SERVICES TO ADOLESCENTS WITH EMOTIONAL AND BEHAVIORAL DISORDERS AT KAKAMEGA REHABILITATION CENTRE, KAKAMEGA COUNTY, KENYA

This study purposely sought to investigate resources used in the provision of services to adolescents with emotional and behavioural disorders. The study adopted a case study design targeting 250 rehabilitees, 30 rehabilitators, and 1 manager. The study used a lottery method to select a sample size of 50% of the target population. The study sample comprised 125 rehabilitees, 15 rehabilitators, and 1 manager making a total of 141 respondents. The semi-structured interview guide for the manager, questionnaires for both rehabilitators and rehabilitees, and observation checklist for resources were used as research instruments. Piloting of the instruments was done at the Shikusa rehabilitation centre. A case study research methodology was used in the study. Data from objectives were analysed both quantitatively and qualitatively. Descriptive statistics for example frequency tables and percentages sum up information measurably from the closed-ended items. The analysed information was introduced utilizing frequency tables, structured presentations, pie charts, and graphs while qualitative data from the manager's semi-structured interview schedule was summarized thematically and narrated in words. The findings indicated that the main material resources available were playing fields, workshops, dormitories, building and construction tools, carpentry tools, classrooms, poultry apparatus, and teaching and learning materials. The study recommends that service providers at the centre need to help the adolescents to achieve a greater sense of independence, and personal responsibility, setting goals, making choices, and understanding their responsibilities which would enhance their self-determination. There is a need for the government to implement strict measures that would ensure that juvenile acts are monitored and youths are protected from any harm. Kenya Institute of Curriculum Development should come up with guidelines on effective ways of managing learners with behaviour disorders while they are still in the childhood stage.&lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt; Article visualizations:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;img src="/-counters-/soc/0029/a.php" alt="Hit counter" /&gt;&lt;/p&gt;

Ethnomedicinal Plants Used by Middle-Aged Residents in San Antonio, Tandag City, Surigao Del Sur, PhilippinesFull Text

People all around the globe are always looking for ways to use plants as medicines to treat various ills and diseases. The study on medicinal plants and their traditional usage is currently popular around the world. Moreover, with the arising diseases and the need for more cost-effective medications, documentation of the claimed medicinal plants by local communities is vital because it will open a lot of opportunities for the discovery and improvement of new and affordable plant-based medicines. In the province of Surigao del Sur Philippines, the older generation are the ones who apply their traditional knowledge on the use of herbal plants. Thus, this study limits on the middle-aged residents in the village of San Antonio, Tandag City in Surigao del Sur Philippines on their use of traditional knowledge in using herbal plants. Forty-six respondents were chosen following the convenient sampling technique. Gathered data on demographic profile of the respondents, plant part used, methods used in the preparation of herbal plant, name of ailments was quantified using descriptive statistics (frequency, sum, and percentage). Likewise, calculation of used value was determined using percentage. Correlation between the age and gender to methods of plant parts used were done using Pearson Correlation. A total of 46 (7 males and 39 females) served as respondents in this study. Highest number of respondents belonged to ages 45 to 49. Almost one third of the respondents residing in the said barangay for 41-50 years. Meanwhile, most of the respondents were using medicinal plants for 1-10 years. It was also found that most of the respondents obtained their source of ethnomedicinal knowledge from their ancestors. Twenty-three medicinal plants from 15 families, the majority of which belonged to the Lamiaceae genus were used as herbal plants. Most of these plants are collected as herbs and shrubs. Leaves are commonly harvested for use and taken orally as decoctions. Viral diseases (cough and cold) were the most dominant ailments treated by the herbal plants. Oregano/Kalabo (Coleus aromaticus) had the highest use-value). It further shows that age is correlated with the changes to the methods of plant preparation while gender is not correlated. The study shows that despite increased urbanization, the village of San Antonio still has a range of plant species with medicinal importance. Thus, in the context of a wider local use as well as possible scientific and pharmaceutical applications, these herbal plants might be further examined for safety and efficacy.