Displaying publications 81 - 93 of 93 in total

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  1. Nayeri ND, Goudarzian AH, Herth K, Naghavi N, Nia HS, Yaghoobzadeh A, et al.
    Int J Health Sci (Qassim), 2020 9 22;14(5):50-57.
    PMID: 32952505
    Objective: The psychological construct of hope is an important determinant for mental health and well-being. The availability of valid and reliable instruments to measure hope is, therefore, critical. Despite a large number of psychometric studies on the Herth Hope Index (HHI), its construct validity has not yet been determined. Therefore, this paper aimed to conduct a systematic review of the psychometric properties of the HHI.

    Methods: Databases such as PubMed, Science Direct, Google Scholar, Magiran, SID, IranDoc, and IranMedex were evaluated systematically using the terms "HHI," "psychometric," "validity," "reliability," and related terms (with the use of OR and AND operators) and no restrictions on the year of publication. A total of 13 eligible studies were found published between 1992 and 2018 in the USA, Portugal, Switzerland, Iran, Germany, Petersburg, Japan, the Netherlands, Lima, Peru, and Norway. The methodology used in the available studies included principal component analysis (n = 6), maximum likelihood estimation (n = 5), and principal axis factoring (n = 1). One study did not point the methodology.

    Results: Four studies reported the total extracted variances to be less than 50%, six studies reported variance between 50% and 60%, and three papers reported variance that exceeded 60%. Of the papers that examined the factor structure of the HHI, two studies reported a one-factor solution, seven reported two factors, and four reported a three-factor solution. Although the HHI is the most widely translated and psychometrically tested tool in languages other than English, psychometric variations in factor solutions remain inconsistent.

    Conclusion: Findings highlight the need for future research that appraises the validity of the HHI in different countries, and how the measure relates to other scales that evaluate hope.

    Matched MeSH terms: Likelihood Functions
  2. Jani J, Mustapha ZA, Ling CK, Hui ASM, Teo R, Ahmed K
    Data Brief, 2020 Dec;33:106388.
    PMID: 33102655 DOI: 10.1016/j.dib.2020.106388
    In 2019, 10 million new cases of tuberculosis have been reported worldwide. Our data reports genetic analyses of a Mycobacterium tuberculosis strain SBH321 isolated from a 31-year-old female with pulmonary tuberculosis. The genomic DNA of the strain was extracted from pure culture and subjected to sequencing using Illumina platform. M. tuberculosis strain SBH321 consists of 4,374,895 bp with G+C content of 65.59%. The comparative analysis by SNP-based phylogenetic analysis using maximum-likelihood method showed that our strain belonging to sublineage of the Ural family of Europe-America-Africa lineage (Lineage 4) and clustered with M. tuberculosis strain OFXR-4 from Taiwan. The whole genome sequence is deposited at DDBJ/ENA/GenBank under the accession WCJH00000000 (SRR10230353).
    Matched MeSH terms: Likelihood Functions
  3. 'Aaishah Radziah Jamaludin, Fadhilah Yusof, Suhartono
    MATEMATIKA, 2020;36(1):15-30.
    MyJurnal
    Johor Bahru with its rapid development where pollution is an issue that needs to be considered because it has contributed to the number of asthma cases in this area. Therefore, the goal of this study is to investigate the behaviour of asthma disease in Johor Bahru by count analysis approach namely; Poisson Integer Generalized Autoregressive Conditional Heteroscedasticity (Poisson-INGARCH) and Negative Binomial INGARCH (NB-INGARCH) with identity and log link function. Intervention analysis was conducted since the outbreak in the asthma data for the period of July 2012 to July 2013. This occurs perhaps due to the extremely bad haze in Johor Bahru from Indonesian fires. The estimation of the parameter will be done by quasi-maximum likelihood estimation. Model assessment was evaluated from the Pearson residuals, cumulative periodogram, the probability integral transform (PIT) histogram, log-likelihood value, Akaike’s Information Criterion (AIC) and Bayesian information criterion (BIC). Our result shows that NB-INGARCH with identity and log link function is adequate in representing the asthma data with uncorrelated Pearson residuals, higher in log likelihood, the PIT exhibits normality yet the lowest AIC and BIC. However, in terms of forecasting accuracy, NB-INGARCH with identity link function performed better with the smaller RMSE (8.54) for the sample data. Therefore, NB-INGARCH with identity link function can be applied as the prediction model for asthma disease in Johor Bahru. Ideally, this outcome can assist the Department of Health in executing counteractive action and early planning to curb asthma diseases in Johor Bahru.
    Matched MeSH terms: Likelihood Functions
  4. Barki N, Choudhry FR, Munawar K
    PMID: 33500886 DOI: 10.47176/mjiri.34.159
    Background: The construct of satisfaction with life has been studied across various cultures through the Satisfaction with Life Scale. The Satisfaction with Life Scale (SWLS) has been validated across several populations and languages. There are no published psychometric properties of its Urdu version. Hence, the aim of this study was to ascertain the psychometric properties of the Urdu version of the SWLS among the Urdu speaking population of Pakistan. Methods: The SWLS has already been translated into Urdu, and the Urdu version is available on the author's website however there is no information about its psychometric properties. To establish the psychometric properties especially the factor structure of the already translated Urdu SWLS, the SWLS-Urdu was administered to Urdu speaking population residing in Pakistan. The statistical analyses (i.e., normality through skewness and kurtosis, Kaiser-Meyer-Olkin (KMO) and Bartlett's test of sphericity, and test and re-test reliability) were conducted through SPSS version 25.0. Structure Equation Modelling via maximum likelihood method of estimation was used to perform confirmatory factor analysis on the data using AMOS 20.0. The significance level was set at p < 0.05. Results: The study was completed by recruiting 120 participants from different universities in Lahore, Pakistan. The sample was equally divided between male and female participants. The mean age of participants was 22.7(3.6) years. Test of the adequacy of the sample through Kaiser-Mayer-Olkin showed KMO=0.88 and Bartlett's test of sphericity (p<0.001). The Cronbach's alpha reliability of the scale was 0.90 and Confirmatory Factor Analysis confirmed a one-factor model as a good fit with strong statistical evidence. No factorial group variances were noticed in male and female participants. Conclusion: This study shows that Urdu SWLS has sound psychometric properties, is linguistically and culturally acceptable, and equally useful in assessing satisfaction with life in the Urdu speaking population.
    Matched MeSH terms: Likelihood Functions
  5. Omer ME, Abu Bakar M, Adam M, Mustafa M
    Asian Pac J Cancer Prev, 2021 Apr 01;22(4):1045-1053.
    PMID: 33906295 DOI: 10.31557/APJCP.2021.22.4.1045
    OBJECTIVE: Cure rate models are survival models, commonly applied to model survival data with a cured fraction. In the existence of a cure rate, if the distribution of survival times for susceptible patients is specified, researchers usually prefer cure models to parametric models. Different distributions can be assumed for the survival times, for instance, generalized modified Weibull (GMW), exponentiated Weibull (EW), and log-beta Weibull. The purpose of this study is to select the best distribution for uncured patients' survival times by comparing the mixture cure models based on the GMW distribution and its particular cases.

    MATERIALS AND METHODS: A data set of 91 patients with high-risk acute lymphoblastic leukemia (ALL) followed for five years from 1982 to 1987 was chosen for fitting the mixture cure model. We used the maximum likelihood estimation technique via R software 3.6.2 to obtain the estimates for parameters of the proposed model in the existence of cure rate, censored data, and covariates. For the best model choice, the Akaike information criterion (AIC) was implemented.

    RESULTS: After comparing different parametric models fitted to the data, including or excluding cure fraction, without covariates, the smallest AIC values were obtained by the EW and the GMW distributions, (953.31/969.35) and (955.84/975.99), respectively. Besides, assuming a mixture cure model based on GMW with covariates, an estimated ratio between cure fractions for allogeneic and autologous bone marrow transplant groups (and its 95% confidence intervals) were 1.42972 (95% CI: 1.18614 - 1.72955).

    CONCLUSION: The results of this study reveal that the EW and the GMW distributions are the best choices for the survival times of Leukemia patients.
    .

    Matched MeSH terms: Likelihood Functions
  6. Hamilton MG
    Heredity (Edinb), 2021 06;126(6):884-895.
    PMID: 33692533 DOI: 10.1038/s41437-021-00421-0
    The cost of parentage assignment precludes its application in many selective breeding programmes and molecular ecology studies, and/or limits the circumstances or number of individuals to which it is applied. Pooling samples from more than one individual, and using appropriate genetic markers and algorithms to determine parental contributions to pools, is one means of reducing the cost of parentage assignment. This paper describes and validates a novel maximum likelihood (ML) parentage-assignment method, that can be used to accurately assign parentage to pooled samples of multiple individuals-previously published ML methods are applicable to samples of single individuals only-using low-density single nucleotide polymorphism (SNP) 'quantitative' (also referred to as 'continuous') genotype data. It is demonstrated with simulated data that, when applied to pools, this 'quantitative maximum likelihood' method assigns parentage with greater accuracy than established maximum likelihood parentage-assignment approaches, which rely on accurate discrete genotype calls; exclusion methods; and estimating parental contributions to pools by solving the weighted least squares problem. Quantitative maximum likelihood can be applied to pools generated using either a 'pooling-for-individual-parentage-assignment' approach, whereby each individual in a pool is tagged or traceable and from a known and mutually exclusive set of possible parents; or a 'pooling-by-phenotype' approach, whereby individuals of the same, or similar, phenotype/s are pooled. Although computationally intensive when applied to large pools, quantitative maximum likelihood has the potential to substantially reduce the cost of parentage assignment, even if applied to pools comprised of few individuals.
    Matched MeSH terms: Likelihood Functions
  7. Foo SK, Cubbidge RP, Heitmar R
    Eur J Ophthalmol, 2021 Jul;31(4):1870-1876.
    PMID: 32468855 DOI: 10.1177/1120672120926455
    BACKGROUND: Numerous fast threshold strategies have been developed in perimetry which use maximum likelihood approaches to estimate the threshold. A recent approach to threshold estimation has been developed estimating the threshold from a limited number of test points which further reduces examination time. This strategy, SPARK, has not been compared to the SITA strategy. The aim of this study was to compare SPARK with SITA in a normal cohort to evaluate within and between strategy agreement in threshold estimates.

    METHODS: A total of 83 normal subjects each underwent two visual field examinations with SITA and SPARK on two separate occasions on a randomly selected eye. The eye examined and the order of strategy examined first was randomised but remained constant over the two perimetry visits.

    RESULTS: Visual field examination with SPARK Precision was on average 33% faster than SITA Standard. A positive correlation between group mean sensitivities of SITA Standard and SPARK Precision (rho = 0.713, p 

    Matched MeSH terms: Likelihood Functions
  8. Althuwaynee OF, Pokharel B, Aydda A, Balogun AL, Kim SW, Park HJ
    J Expo Sci Environ Epidemiol, 2021 07;31(4):709-726.
    PMID: 33159165 DOI: 10.1038/s41370-020-00271-8
    Accurate identification of distant, large, and frequent sources of emission in cities is a complex procedure due to the presence of large-sized pollutants and the existence of many land use types. This study aims to simplify and optimize the visualization mechanism of long time-series of air pollution data, particularly for urban areas, which is naturally correlated in time and spatially complicated to analyze. Also, we elaborate different sources of pollution that were hitherto undetectable using ordinary plot models by leveraging recent advances in ensemble statistical approaches. The high performing conditional bivariate probability function (CBPF) and time-series signature were integrated within the R programming environment to facilitate the study's analysis. Hourly air pollution data for the period between 2007 to 2016 is collected using four air quality stations, (ca0016, ca0058, ca0054, and ca0025), situated in highly urbanized locations that are characterized by complex land use and high pollution emitting activities. A conditional bivariate probability function (CBPF) was used to analyze the data, utilizing pollutant concentration values such as Sulfur dioxide (SO2), Nitrogen oxides (NO2), Carbon monoxide (CO) and Particulate Matter (PM10) as a third variable plotted on the radial axis, with wind direction and wind speed variables. Generalized linear model (GLM) and sensitivity analysis are applied to verify and visualize the relationship between Air Pollution Index (API) of PM10 and other significant pollutants of GML outputs based on quantile values. To address potential future challenges, we forecast 3 months PM10 values using a Time Series Signature statistical algorithm with time functions and validated the outcome in the 4 stations. Analysis of results reveals that sources emitting PM10 have similar activities producing other pollutants (SO2, CO, and NO2). Therefore, these pollutants can be detected by cross selection between the pollution sources in the affected city. The directional results of CBPF plot indicate that ca0058 and ca0054 enable easier detection of pollutants' sources in comparison to ca0016 and ca0025 due to being located on the edge of industrial areas. This study's CBPF technique and time series signature analysis' outcomes are promising, successfully elaborating different sources of pollution that were hitherto undetectable using ordinary plot models and thus contribute to existing air quality assessment and enhancement mechanisms.
    Matched MeSH terms: Likelihood Functions
  9. Selvaraj S, Naing NN, Wan-Arfah N, de Abreu MHNG
    PMID: 34360201 DOI: 10.3390/ijerph18157910
    The aim of this study was to evaluate the performance of a set of sociodemographic and habits measures on estimating periodontal disease among south Indian adults. This cross-sectional study was carried out among 288 individuals above 18 years old in Tamil Nadu, India. The outcome of the study was periodontal disease, measured by WHO criteria. The covariates were age, ethnicity, smoking and alcohol habit. The assessment of factors predicting periodontal disease was carried out by multiple logistic regression analysis using R version 3.6.1. The demographic factors like age group (AOR = 3.56; 95% CI 1.69-7.85), ethnicity (AOR = 6.07; 95% CI 2.27-18.37), non-alcoholic (AOR = 0.31; 95% CI 0.13-0.64) and non-smoking (AOR = 0.33; 95% CI 0.15-0.67) were found to be associated with the outcome. The maximum log likelihood estimate value was -30.5 and AIC was 385 for the final model, respectively. Receiver operating characteristic (ROC) curve for the periodontal disease was 0.737. We can conclude that sociodemographic factors and habits were useful for predicting periodontal diseases.
    Matched MeSH terms: Likelihood Functions
  10. Nur Aisyah Atikah Alizan, Sarah S. Zakaria
    MyJurnal
    Bacteria of the genus Komagataeibacter are described to be the most noteworthy for having several of its species being efficient and strong cellulose producers. The 16S ribosomal RNA (rRNA) gene analysis is often used for the identification and taxonomic classification of these bacteria species. In order to observe the phylogenetic relationship among Komagataeibacter sp., twelve sequences of the 16S rRNA gene with three sequences each for species namely Komagataeibacter europaeus, Komagataeibacter hansenii, Komagataeibacter intermedius and Komagataeibacter xylinus were retrieved from NCBI GenBank database. The sequences were aligned and analysed using PAUP, OrthoANI and BLAST, followed by the phylogenetic tree construction using a Maximum Likelihood method. The parsimony character diagnostic analysis showed very few numbers of parsimony- informative characters present in the aligned sequences which is only 1.5% of the total characters. The inferred phylogenetic relationships demonstrated the unexpected positioning of K. xylinus (GQ240638: Gluconacetobacter xylinus strain) and K. xylinus (KC11853: G. xylinus strain) into the clades of K. europaeus and K. hansenii respectively. The also very low bootstrap values of the branch points linking the K. europaeus species indicated low support for the produced topologies. The findings of this study indicate that more phylogenies information can be attained by increasing the taxon sampling. In addition, more robust molecular data are needed to infer the phylogenetic relationships between the Komagataeibacter species more accurately.
    Matched MeSH terms: Likelihood Functions
  11. Trimarsanto H, Amato R, Pearson RD, Sutanto E, Noviyanti R, Trianty L, et al.
    Commun Biol, 2022 Dec 23;5(1):1411.
    PMID: 36564617 DOI: 10.1038/s42003-022-04352-2
    Traditionally, patient travel history has been used to distinguish imported from autochthonous malaria cases, but the dormant liver stages of Plasmodium vivax confound this approach. Molecular tools offer an alternative method to identify, and map imported cases. Using machine learning approaches incorporating hierarchical fixation index and decision tree analyses applied to 799 P. vivax genomes from 21 countries, we identified 33-SNP, 50-SNP and 55-SNP barcodes (GEO33, GEO50 and GEO55), with high capacity to predict the infection's country of origin. The Matthews correlation coefficient (MCC) for an existing, commonly applied 38-SNP barcode (BR38) exceeded 0.80 in 62% countries. The GEO panels outperformed BR38, with median MCCs > 0.80 in 90% countries at GEO33, and 95% at GEO50 and GEO55. An online, open-access, likelihood-based classifier framework was established to support data analysis (vivaxGEN-geo). The SNP selection and classifier methods can be readily amended for other use cases to support malaria control programs.
    Matched MeSH terms: Likelihood Functions
  12. Foo CH
    Math Biosci Eng, 2023 Jul 03;20(8):14487-14501.
    PMID: 37679145 DOI: 10.3934/mbe.2023648
    Crustaceans exhibit discontinuous growth as they shed hard shells periodically. Fundamentally, the growth of crustaceans is typically assessed through two key components, length increase after molting (LI) and time intervals between consecutive molts (TI). In this article, we propose a unified likelihood approach that combines a generalized additive model and a Cox proportional hazard model to estimate the parameters of LI and TI separately in crustaceans. This approach captures the observed discontinuity in individuals, providing a comprehensive understanding of crustacean growth patterns. Our study focuses on 75 ornate rock lobsters (Panulirus ornatus) off the Torres Strait in northeastern Australia. Through a simulation study, we demonstrate the effectiveness of the proposed models in characterizing the discontinuity with a continuous growth curve at the population level.
    Matched MeSH terms: Likelihood Functions
  13. Zanti M, O'Mahony DG, Parsons MT, Li H, Dennis J, Aittomäkkiki K, et al.
    Hum Mutat, 2023;2023.
    PMID: 38725546 DOI: 10.1155/2023/9961341
    A large number of variants identified through clinical genetic testing in disease susceptibility genes, are of uncertain significance (VUS). Following the recommendations of the American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP), the frequency in case-control datasets (PS4 criterion), can inform their interpretation. We present a novel case-control likelihood ratio-based method that incorporates gene-specific age-related penetrance. We demonstrate the utility of this method in the analysis of simulated and real datasets. In the analyses of simulated data, the likelihood ratio method was more powerful compared to other methods. Likelihood ratios were calculated for a case-control dataset of BRCA1 and BRCA2 variants from the Breast Cancer Association Consortium (BCAC), and compared with logistic regression results. A larger number of variants reached evidence in favor of pathogenicity, and a substantial number of variants had evidence against pathogenicity - findings that would not have been reached using other case-control analysis methods. Our novel method provides greater power to classify rare variants compared to classical case-control methods. As an initiative from the ENIGMA Analytical Working Group, we provide user-friendly scripts and pre-formatted excel calculators for implementation of the method for rare variants in BRCA1, BRCA2 and other high-risk genes with known penetrance.
    Matched MeSH terms: Likelihood Functions
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