Standard Statistical Software Research Articles

Learning about treatment effects in a new target population under transportability assumptions for relative effect measures.

Investigators often believe that relative effect measures conditional on covariates, such as risk ratios and mean ratios, are "transportable" across populations. Here, we examine the identification of causal effects in a target population using an assumption that conditional relative effect measures are transportable from a trial to the target population. We show that transportability for relative effect measures is largely incompatible with transportability for difference effect measures, unless the treatment has no effect on average or one is willing to make even stronger transportability assumptions that imply the transportability of both relative and difference effect measures. We then describe how marginal (population-averaged) causal estimands in a target population can be identified under the assumption of transportability of relative effect measures, when we are interested in the effectiveness of a new experimental treatment in a target population where the only treatment in use is the control treatment evaluated in the trial. We extend these results to consider cases where the control treatment evaluated in the trial is only one of the treatments in use in the target population, under an additional partial exchangeability assumption in the target population (i.e., an assumption of no unmeasured confounding in the target population with respect to potential outcomes under the control treatment in the trial). We also develop identification results that allow for the covariates needed for transportability of relative effect measures to be only a small subset of the covariates needed to control confounding in the target population. Last, we propose estimators that can be easily implemented in standard statistical software and illustrate their use using data from a comprehensive cohort study of stable ischemic heart disease.

Optimisation of the composition of safe dental gel with IL-1β antagonist for the treatment of inflammatory periodontal diseases

Aim. The study aims to develop the composition of the oromucosal gel with the IL-1β interleukin antagonist for complex treatment of inflammatory periodontal diseases. Materials and methods. Experimental studies were conducted based on the Department of Medicines Technology of Zaporizhzhia State Medical and Pharmaceutical University and the Training Medical and Laboratory Center of Zaporizhzhia State Medical and Pharmaceutical University of the Ministry of Health of Ukraine. As an active component, in the recipe of oromucosal gel, used antagonist of the interleukin IL-1B. Excipients: D-panthenol (the plasticizer), carboxymethylcellulose sodium salt (the viscosity modifier and mucoadhesive component), Tween-80 (the enhancer absorption), benzalkonium chloride (the preservative), sodium hydrophosphate + citric acid (the phosphate buffer solution), purified water. The experiments used existing and auxiliary ingredients of pharmaceutical purity, which were obtained from Sinbias LLC, Istok-Plus LLC, LLC “Mobile Medical”. For the design of the experiment, the methodology of the response surface (Box-Behnken Design) is used: Na CMC, Tween-80, D-panthenol; and four answers: pH, viscosity test, system type, mucoadhesive properties. Research methods: rheological research (viscosity test, amplitude test, frequency test, mucoadhesive test, thixotropy test) performed in oscillation mode on the modular compact Rheometer Anton Paar MCR 302 (CP50-1 SN71317), which, compared to cylindrical devices, requires a much smaller amount of gel sample and allows the planned tests in the oscillation mode, the temperature in the experiments was provided with a built-in thermostat (Peltier Temperature Control, C-PTD 200). Pharmaco-toxicological studies were conducted on 46 white outbred rats of both sexes, weighing 160–180 grams, which were received from Vivarium by the Institute of Pharmacology and Toxicology. The studies were performed on enough animals, all manipulations were carried out by the provisions on the use of animals in biomedical experiments. The results of the study were calculated using the standard statistical package of the Statistica for Windows 13 (StatSoft Inc., No. JPZ804I382130ARCN10-J), as well as SPSS 16.0, Microsoft Office Excel 2003. Results. According to the design of the experiment, it is established that the components of the system do not change the value of pH in experimental oromucosal gels (6.5500 ± 0.0334). The Anova for Quadratic Model statistical analysis data certify the significant impact of Na CMC, and Tween-80 factors on the viscous characteristics of oromucosal gels (F-value > p-value). Comparison of mucoadhesive characteristics of the studied samples of oromucosal gels was made using dynamic mechanical analysis and the results of statistical analysis of ANOVA for Quadratic Model highlight the significant influence of Na CMC, D-panthenol, Tween-80. Optimized oromucosal gel test data is obtained that its structure is restored after the applied effort, namely the restoration of the structure after 10 seconds occurs by 69.5 %, after 30 s by 76.1 %, after 180 s by 85.4 %, after 180 s which allows to predict the stability of the dosage form, both after manufacture and after use. Conclusions. The composition of the oromucosal gel of anti-inflammatory action with the IL-1β interleukin antagonist for the complex treatment of inflammatory diseases of periodontal is developed. The optimized composition of the oromucosal gel obtained has satisfactory performance of kinetic stability and thixotropic properties. The developed gel for dentistry meets all the requirements for harmlessness and safety for dosage forms of this group toxicity, lack of local irritant and allergic action.

To Determine the Blood Group Correlation among the Cases of Dysvascular Amputation: Retrospective Study

Abstract Objective: The objective of the study was to identify the association of specific blood group among the cases of dysvascular amputation. Introduction: Literature showed the association of certain blood group with increased cardiovascular risk and other thrombotic vascular diseases in addition to increased gastric cancer risk and periodontal disease. By the way of extending the relation between blood group and atherosclerosis, this study aims to find out if there is any correlation between blood group and dysvascular amputation. Materials and Methods: Retrospective analysis of patient records with sample size of 100 is considered for this study. Sample population included was patients with lower limb amputation due to dysvascular etiology, who were admitted for prosthesis for a period of 1 year at Government Institute of Rehabilitation Medicine. Statistical analysis was performed using the standard statistical software. Results: Analysis showed that there is a correlation between non-O blood group and dysvascular amputation compared to O group. Among non-O group, population with B +ve has higher incidence of amputation as analysed from the study. Conclusion: This study reveals that there is a strong correlation between dysvascular amputation and non-O blood group. Focus on the prevention of modifiable risk factors may reduce the incidence of amputation for risk-prone blood group.

Profile of patients presenting at the echocardiography laboratory of a tertiary institution in the central region of South Africa

Introduction: Worldwide cardiovascular disease is associated with substantial economic challenges and profound morbidity and mortality. Considering the dearth of information for the central region of South Africa, this study aimed to assess the profile of patients who were referred to an echocardiography laboratory at a tertiary institution. Methods: A hospital-based, observational, descriptive study was conducted. Demographic, anthropometric, socio-economic, clinical and echocardiographic data were collected. Patients were categorised by hospitalisation status and reason for referral. Standard transthoracic echocardiograms were performed. Data were analysed using standard statistical software. Results: The study population had a mean age of 51.8±17.38 years, was predominantly black (64%) with a slight female preponderance (55%). The majority of patients were from a low-socioeconomic background (H0-H2; 91%). Most patients were from the Mangaung district (37%) and the referral pattern showed that regions with more hospitals tend to refer more patients for echocardiography. Alarmingly, two-thirds of the study population were hypertensive (64%) and 57% had a body mass index exceeding 25 kg/m2. Cardiology referred most patients for echocardiography (49%) and inpatient and outpatient referrals were almost equal (48% vs 52%). Abnormal echocardiographic findings were reported in 74% of patients with myocardial dysfunction being the most significant pathology (73%). Sixty-three percent of referrals were for routine echocardiographic assessment. Conclusion: This is the first study describing the profile of patients referred for echocardiography in the central region of South Africa. Travel distances and obtainability of health services appeared to have impacted referral patterns. Specific patterns of disease related to the individual referring specialist health care services. Hospitalisation status did not influence referrals.

Comparison of aggressiveness in central versus peripheral T1a clear-cell renal cell carcinoma

PurposeThis study aimed to estimate the difference between peripheral and central small renal lesions in terms of their oncologic potential. MethodsCross-sectional retrospective analysis of patients with small renal masses (T1a) who underwent surgical treatment between January 2008 and July 2019 at the affiliated hospital. Only patients with ccRCC pathology were included. Cases were divided into 2 groups depending on tumor location (central or peripheral) based on the R.E.N.A.L and local nephrometry scoring. Presence of nodal involvement, distant metastases, ISUP grade and endophytic growth were defined as aggressiveness predictors. Statistical analyses was performed using a standard statistical software (IBM SPPS Statistics Ver. 22), with P < 0.05 considered statistically significant. Associations between tumor location and Fuhrman grade, exo-/endophytic growth, TNM classification, and type of operation were tested using the Pearson χ² test and 1-way ANOVA test. ResultsPatients with centrally located tumors had a higher incidence of clinical and pathological lymph node involvement (P = 0.02, χ2 = 5.1). Patients in both groups had an equal number of distant metastases at the time of diagnosis (P = 0.3, χ2 = 0.8). The operation time was significantly longer in patients with central lesions, which obviously showed higher tumor complexity in this group (P < 0.005). Pathological evaluation revealed differences between ISUP grades in both groups (P < 0.005, χ2 = 29.9). Central masses were characterized by higher aggressiveness, indicating a worse prognosis. Furthermore, the cases in the first group were more often endophytic (P = 0.03, χ2 = 0.9). Nevertheless, this did not affect the surgical strategy in most cases with a tendency toward partial nephrectomy. Eventually, organ-sparing treatment was preferable in both groups (P = 0.13, χ2 = 2.29). ConclusionCentrally located kidney cancer has showed in present study a higher incidence of high ISUP grade, regional nodal involvement and endophytic growth type. Endophytic growth type was associated with worse ISUP grading. Distribution of ISUP grade was not age depended, thus showing no difference by this criterion, when comparing different age groups. Higher ISUP grade was strongly associated with presence of distant metastases in T1a kidney tumors. Further analysis is needed to investigate aggressiveness of centrally located T1a RCC, as it may influence current conservative management options.

Association analysis of self-reported outcomes with a validated subset.

In health-science research, outcomes ascertained through surveys and interviews are subject to potential bias with respect to the true outcome status, which is only ascertainable with clinical and laboratory assessment. This measurement error may lead to biased inference when evaluating associations between exposures and outcomes of interest. Here, we consider a cohort study in which the outcome of interest is ascertained via questionnaire, subject to imperfect ascertainment, but where a subset of participants also have a clinically assessed, validated outcome available. This presents a methodological opportunity to address potential bias. Specifically, we constructed the likelihood in two parts, one using the validated subset and the other using a subset without validation. This work expands on that proposed by Pepe and enables inference with standard statistical software. Weighted generalized linear model estimates for our method and maximum likelihood estimates (MLE) for Pepe's method were computed, and the statistical inference was based on the standard large-sample likelihood theory. We compare the finite sample performance of two approaches through Monte Carlo simulations. This methodological work was motivated by a large cohort study of long-term childhood cancer survivors, allowing us to provide a relevant application example where we examined the association between clinical factors and chronic health conditions.

Leveraging homologous hypotheses for increased efficiency in tumor growth curve testing

In this note, we present an innovative approach called “homologous hypothesis tests” that focuses on cross-sectional comparisons of average tumor volumes at different time-points. By leveraging the correlation structure between time-points, our method enables highly efficient per time-point comparisons, providing inferences that are highly efficient as compared to those obtained from a standard two-sample t test. The key advantage of this approach lies in its user-friendliness and accessibility, as it can be easily employed by the broader scientific community through standard statistical software packages.

Influence of experimental heart failure therapy with different generations of β-adrenergic blockers on Cardiac Electrical Activity (ECG) and Autonomic Regulation of Heart Rhythm (ARHR)

Abstract: In the complex treatment of chronic heart failure (CHF) β-adrenoblockers (carvedilol, nebivolol, bisoprolol, metoprolol) are used, which due to their pharmacological properties increase the survival rate of patients, improve cardio- and haemodynamic parameters, metabolism. However, modern realities in medicine require creation of new more effective and safe β-adrenoblockers. In this regard, the potential drug Hypertirl is of interest. The aim was to evaluate the cardioprotective effect of 1-(b-phenylethyl)-4-amino-1,2,4-triazolium bromide (Hypertril) on cardiac electrical activity and autonomic regulation of heart rhythm in a model of CHF in comparison with β-adrenoblockers of different generations (Nebivolol, Carvedilol, Bisoprolol, Metoprolol). Materials and methods: Chronic heart failure was induced by 14-day administration of doxorubicin in a cumulative dose of 15 mg/kg to white mongrel rats weighing 190–220g (total 85). The investigated drugs were administered after doxorubicin course for 30 days: Hypertril at an experimentally substantiated dose of 3.5 mg/kg, Metoprolol succinate 15 mg/kg, Nebivolol 10 mg/kg, Carvedilol 50 mg/kg, Bisoprolol 10 mg/kg. At the end of drug administration under thiopental anaesthesia (40 mg/kg), electrocardiogram (ECG) and autonomic regulation of heart rhythm (ARHR) were analysed using a computer analyser CardioCom-2000plus (KAI-Medica, Ukraine). The results of the study were calculated using a standard statistical package “STATISTICA for Windows 6.0” (StatSoftInc., №AXXR712D833214FAN5), “SPSS 16.0” and “Microsoft Office Excell 2003”. Results and discussion: Hypertril administration resulted in a negative chronotropic effect, normalisation of atrial (P) and ventricular (R) spike amplitude, ST segment inversion below isoline, increased amplitude of ventricular myocardial repolarisation T. Myocardial repolarisation spike were observed, as well as normalised the duration of atrial (P) and ventricular depolarisation phase (QRS complex) to the intact value and restored the duration of electrical diastole (TR interval). Hypertril reduced systolic and diastolic myocardial dysfunction in animals with CHF. Hypertril restored autonomic mechanisms of heart rhythm regulation and balanced activity of sympathetic and parasympathetic parts of autonomic nervous system in the control of cardiac function. Conclusion: The obtained results demonstrated the undoubted advantage of the new original molecule (Hypertril) over basic β-adrenoblockers (Metoprolol, Nebivolol, Carvedilol and Bisoprolol) and experimentally justify further in-depth study to create on its basis a drug for the treatment of CHF.

Empowering Women in Agriculture: Exploring Their Role and Decision Making Impact – A Study in Manipur, India

Background: Manipur, a North-Eastern State of India where about 49.81 per cent of total population is women [1] and they contribute about 51.46 per cent of total working force. The state, which is relatively backward in agricultural development paradigm, has a glorious past regarding women’s ‘movement’ for the state’s cause. Now, it is to be understood properly their role and participation in farm economy for revamping the agrarian situation in the state by exploring the farm women’s role.&#x0D; Methods: The study was conducted by collecting both secondary as well as primary information from sample respondents equally distributed over two valley districts (namely, Thoubal and Imphal East) of Manipur. In all the phases of selection (of sub-division, block, village etc.) the method of probability proportional sampling was employed. Standard econometric methods and statistical packages were applied to elucidate the core objective(s) of the study.&#x0D; Results: The status of participation of farm women in decision making process has been judged with the help of Participatory Index (P.I) and Decision Making Index (DMI). Farm women, in general, participates prominently in socio-cultural matters (DMI = 0.86-0.93) and miscellaneous matters (DMI = 0.83-0.96), moderately in family’s financial/economic matters (DMI = 0.62-0.89) but rather poorly (DMI = 0.43-0.56) in farming matters. More specifically, they are relatively less consulted or are given less importance on matters like consultation with officials (private or government), purchase of household furniture, purchase of improved implements/machineries, selection of crop variety, input management in crop cultivation etc.

The impact of integrating a compulsory community-oriented research program within undergraduate medical curriculum on graduates' scientific publications: perspectives from Arabian Gulf University

PurposeMedical schools aspire to graduate doctors who are competent in interpreting, conducting and publishing scientific research. Hence, the purpose of the paper is explore the impact of a structured compulsory community-oriented, project-based research program in the undergraduate medical curriculum on medical graduates’ future careers, publications and motivation for scientific research.Design/methodology/approachAn online questionnaire was sent through the Alumni Association of the Arabian Gulf University (AGU) to medical graduates who have valid email addresses, seeking information on their scientific productivity along with demographic and current employment data. Responses were collated and analyzed using a standard statistical software package. The chi-square test and p-value were calculated. P-value &lt;0.05 was considered statistically significant.FindingsCompleted forms were received from 91 medical graduates. In this sample, almost a quarter of the respondents have published a research paper out of their undergraduate research project, and about 50% have published at least one paper (as main or co-author) after graduation. Both demographic and medical specialty was not related to the doctor's perception of the benefits they have attained from the compulsory undergraduate research program. However, medical graduates who are at senior levels in their medical careers and those who are employed in secondary healthcare are significantly more likely to publish research papers.Originality/valueThe compulsory community-oriented, project-based research program in AGU has positively contributed to the research productivity of graduates, and it would be worthwhile to include such programs as an integral part of the undergraduate medical curriculum.

Interindividual variations in associative visual learning: Exploration, description, and partition of response characteristics.

Relying on existing literature to identify suitable techniques for characterizing individual differences presents practical and methodological challenges. These challenges include the frequent absence of detailed descriptions of raw data, which hinders the assessment of analysis appropriateness, as well as the exclusion of data points deemed outliers, or the reliance on comparing only extreme groups by categorizing continuous variables into upper and lower quartiles. Despite the availability of algorithmic modeling in standard statistical software, investigations into individual differences predominantly focus on factor analysis and parametric tests. To address these limitations, this application-oriented study proposes a comprehensive approach that leverages behavioral responses through the use of signal detection theory and clustering techniques. Unlike conventional methods, signal detection theory considers both sensitivity and bias, offering insights into the intricate interplay between perceptual ability and decision-making processes. On the other hand, clustering techniques enable the identification and classification of distinct patterns within the dataset, allowing for the detection of singular behaviors that form the foundation of individual differences. In a broader framework, these combined approaches prove particularly advantageous when analyzing large and heterogeneous datasets provided by data archive platforms. By applying these techniques more widely, our understanding of the cognitive and behavioral processes underlying learning can be expedited and enhanced.

Estimator of Agreement with Covariate Adjustment

The parameter κ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\kappa $$\\end{document} is a general agreement structure used across many fields, such as medicine, machine learning and the pharmaceutical industry. A popular estimator for κ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\kappa $$\\end{document} is Cohen’s κ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\kappa $$\\end{document}; however, this estimator does not account for multiple influential factors. The primary goal of this paper is to propose an estimator of agreement for a binary response using a logistic regression framework. We use logistic regression to estimate the probability of a positive evaluation while adjusting for factors. These predicted probabilities are then used to calculate expected agreement. It is shown that ignoring needed adjustment measures, as in Cohen’s κ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\kappa $$\\end{document}, leads to an inflated estimate of κ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\kappa $$\\end{document} and a situation similar to Simpson’s paradox. Simulation studies verified mathematical relationships and confirmed estimates are inflated when necessary covariates are left unadjusted. Our method was applied to an Alzheimer’s disease neuroimaging study. The proposed approach allows for inclusion of both categorical and continuous covariates, includes Cohen’s κ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\kappa $$\\end{document} as a special case, offers an alternative interpretation, and is easily implemented in standard statistical software.

Transportability of causal inference under random dynamic treatment regimes for kidney-pancreas transplantation.

A difficult decision for patients in need of kidney-pancreas transplant is whether to seek a living kidney donor or wait to receive both organs from one deceased donor. The framework of dynamic treatment regimes (DTRs) can inform this choice, but a patient-relevant strategy such as "wait for deceased-donor transplant" is ill-defined because there are multiple versions of treatment (i.e., wait times, organ qualities). Existing DTR methods average over the distribution of treatment versions in the data, estimating survival under a "representative intervention." This is undesirable if transporting inferences to a target population such as patients today, who experience shorter wait times thanks to evolutions in allocation policy. We, therefore, propose the concept of a generalized representative intervention (GRI): a random DTR that assigns treatment version by drawing from the distribution among strategy compliers in the target population (e.g., patients today). We describe an inverse-probability-weighted product-limit estimator of survival under a GRI that performs well in simulations and can be implemented in standard statistical software. For continuous treatments (e.g., organ quality), weights are reformulated to depend on probabilities only, not densities. We apply our method to a national database of kidney-pancreas transplant candidates from 2001-2020 to illustrate that variability in transplant rate across years and centers results in qualitative differences in the optimal strategy for patientsurvival.

Researcher capacity estimation based on the Q model: a generalized linear mixed model perspective

Chance models of scientific creative productivity allow estimation of researcher capacity. One prominent such model is the Q model in which the impact of a scholarly work is modeled as a multiplicative function of researcher capacity and a potential impact (i.e., luck) parameter. Previous work estimated researcher capacity based on an approximation of the Q parameter. In this work, however, I outline how the Q model can be estimated within the framework of generalized linear mixed models. This way estimates of researcher capacity (and all other parameters of the Q model) are readily available and obtained by standard statistical software packages. Usage of such software further allows comparing different distributional assumptions and calculation of reliability of the Q parameter (i.e., researcher capacity). This is illustrated for a large dataset of multidisciplinary scientists (N = 20,296). The Poisson Q model was found to have negligibly better predictive accuracy than the original normal Q model. Reliability estimates revealed excellent reliability of Q estimates with conditional reliability being mostly in acceptable ranges. Reliability of Q parameter estimates further depended heavily on the number of publications of a scientist with reliability increasing with the number of papers. The future and limitations of the Q model in the context of researcher capacity estimation are thoroughly discussed.

Significance Bands for Local Projections

An impulse response function describes the dynamic evolution of an outcome variable following a stimulus or treatment. A common hypothesis of interest is whether the treatment affects the outcome. We show that this hypothesis is best assessed using significance bands rather than relying on commonly displayed confidence bands. Under the null hypothesis, we show that significance bands are trivial to construct with standard statistical software using the LM principle, and should be reported as a matter of routine when displaying impulse responses graphically.

An Approach for the Optimization of Thermal Conductivity and Viscosity of Hybrid (Graphene Nanoplatelets, GNPs: Cellulose Nanocrystal, CNC) Nanofluids Using Response Surface Methodology (RSM).

Response surface methodology (RSM) is used in this study to optimize the thermal characteristics of single graphene nanoplatelets and hybrid nanofluids utilizing the miscellaneous design model. The nanofluids comprise graphene nanoplatelets and graphene nanoplatelets/cellulose nanocrystal nanoparticles in the base fluid of ethylene glycol and water (60:40). Using response surface methodology (RSM) based on central composite design (CCD) and mini tab 20 standard statistical software, the impact of temperature, volume concentration, and type of nanofluid is used to construct an empirical mathematical formula. Analysis of variance (ANOVA) is applied to determine that the developed empirical mathematical analysis is relevant. For the purpose of developing the equations, 32 experiments are conducted for second-order polynomial to the specified outputs such as thermal conductivity and viscosity. Predicted estimates and the experimental data are found to be in reasonable arrangement. In additional words, the models could expect more than 85% of thermal conductivity and viscosity fluctuations of the nanofluid, indicating that the model is accurate. Optimal thermal conductivity and viscosity values are 0.4962 W/m-K and 2.6191 cP, respectively, from the results of the optimization plot. The critical parameters are 50 °C, 0.0254%, and the category factorial is GNP/CNC, and the relevant parameters are volume concentration, temperature, and kind of nanofluid. From the results plot, the composite is 0.8371. The validation results of the model during testing indicate the capability of predicting the optimal experimental conditions.

Bayesian hierarchical response time modelling-A tutorial.

Response time modelling is developing rapidly in the field of psychometrics, and its use is growing in psychology. In most applications, component models for response times are modelled jointly with component models for responses, thereby stabilizing estimation of item response theory model parameters and enabling research on a variety of novel substantive research questions. Bayesian estimation techniques facilitate estimation of response time models. Implementations of these models in standard statistical software, however, are still sparse. In this accessible tutorial, we discuss one of the most common response time models-the lognormal response time model-embedded in the hierarchical framework by van der Linden (2007). We provide detailed guidance on how to specify and estimate this model in a Bayesian hierarchical context. One of the strengths of the presented model is its flexibility, which makes it possible to adapt and extend the model according to researchers' needs and hypotheses on response behaviour. We illustrate this based on three recent model extensions: (a) application to non-cognitive data incorporating the distance-difficulty hypothesis, (b) modelling conditional dependencies between response times and responses, and (c) identifying differences in response behaviour via mixture modelling. This tutorial aims to provide a better understanding of the use and utility of response time models, showcases how these models can easily be adapted and extended, and contributes to a growing need for these models to answer novel substantive research questions in both non-cognitive and cognitive contexts.

COMPARATIVE STUDY ON NUTRITIONAL AND ANTI NUTRITIONAL COMPOSITION OF FRESH AND DRIED OKRA OBTAINED FROM GUSAU MARKET NIGERIA

Okra or commonly known in its Latin as abelmoschus esculentus are one of the green vegetables that is most consumed around the world and is utilized as medicine. Due to post-harvest losses, inadequate storage facilities lead to customers losing fresh okra. Therefore, farmers use traditional drying preservation methods by utilizing solar heat. The research objectives is to identify and evaluate the antinutrient, mineral, and proximate compositions of fresh and dried okra obtained from Gusau Market in Nigeria. Researchers analyzed and compared the samples using standard analytical methods and statistical packages from IBM SPSS version 21. The analysis revealed that the fresh and dried okra samples had the following amounts of water, ash, protein, fiber, carbs, lipids, and total energy: 75.30-8.56%; 1.85-8.05%; 16.44-77.25%; 4.30-2.03%; 0.18-3.15%; 1.93-0.96%; and 56.11-325.76%. While concentrations of mineral elements of fresh and dried okra are 98.22-97.80; 5.45-4.45; 9.75-9.35; 78.52-69.35; 21.36-19.26; and 30.52-29.60 in mg/100g respectively. The phytochemical screening shows the presence of Tannin, Oxalate, Phytate, Saponin, Phenolic, Flavonoid and Alkaloid. For sampling of fresh and dried okra, the amounts of flavonoid and alkaloid in mg/100g are 18.6-17.95 and 10.64-15.14, respectively. There is no significance different in proximate, mineral elements and anti nutritional content between fresh and dried okra samples. Therefore, the researchers can decide that the traditional way by utilizing solar heat is still being utilised by most of farmers. The appropriate method for farmers to prevent lossing okra when post-harvest is having conducive environment for them in order to avoid possible contamination.

Confirmatory Factor Analyses in Psychological Test Adaptation and Development

Confirmatory Factor Analyses in Psychological Test Adaptation and Development

Detecting and Correcting for Separation in Strategic Choice Models

AbstractSeparation or “perfect prediction” is a common problem in discrete choice models that, in practice, leads to inflated point estimates and standard errors. Standard statistical packages do not provide clear advice on how to correct these problems. Furthermore, separation can go completely undiagnosed in fitting advanced models that optimize a user-supplied log-likelihood rather than relying on pre-programmed estimation procedures. In this paper, we both describe the problems that separation can cause and address the issue of detecting it in empirical models of strategic interaction. We then consider several solutions based on penalized maximum likelihood estimation. Using Monte Carlo experiments and a replication study, we demonstrate that when separation is detected in the data, the penalized methods we consider are superior to ordinary maximum likelihood estimators.