Model Fit Research Articles

Construction of A Geographically Weighted Nonparametric Regression Model Fit Test

One of the approach of Geographically Weighted Regression (GWR) models is the Geographically Weighted Nonparametric Regression (GWNR) has more parameters than the GWR model. Models with more parameters usually have better match values, which is an advantage, while models with fewer parameters have the advantage of being easier to use and interpret. However, a model with more parameters should be used if it is proven to be significantly superior. Therefore, the purpose of this study was to develop a hypothesis test of goodness of fit test for GWNR model. The goodness of fit test was performed for the real data. We found that the GWNR model was more suitable than the mixed nonparametric regression model. Some highlights of the proposed method are:• A new model for GWR to overcome the unknown regression function by using mixed estimator spline truncated and fourier series at nonparametric regression• Goodness of fit for GWNR to testing the model fit between the mixed nonparametric regression model and GWNR• Applied goodness of fit test to poverty data in Sulawesi Island and infant mortality in East Java

Family support, need for achievement, and entrepreneurial orientation on entrepreneurial intentions in vulnerable groups

This study aims to design and test the goodness of fit of a theoretical model that describes the effect of family support, need for achievement, and entrepreneurial orientation on entrepreneurial intentions with empirical data in the field. Research participation used subjects totaling 66 people from Ngalang village who were female, did not have permanent jobs, and were included in the poor category. Data collection uses four measurement scales: the entrepreneurial intention scale, family support scale, need for achievement scale, and entrepreneurial orientation scale, and is analyzed using partial least square (PLS) via smartPLS 3.0. The results of the study show the formation of a theoretical model of the influence of family support, need for achievement, and entrepreneurial orientation on entrepreneurial intentions that fit with empirical data. Family support has a positive and very significant effect on entrepreneurial intentions, the need for achievement does not affect an entrepreneurial orientation, and entrepreneurial orientation has a positive and very significant impact on entrepreneurial intentions. This research implies that this model can be used as a reference and applied to overcoming economic problems in vulnerable groups.

Psychometric Evaluation of the “Providing Validation” Measure in Vascular Anomalies

We assessed the psychometric properties of the “providing validation” subscale of PedCOM measures for parents of children with vascular anomalies and adult patients. A total of 139 adult patients and 78 parents completed surveys. The mean score for patients was 3.7 (standard deviation 1.0), and for parents was 4.0 (standard deviation 0.9). “Providing validation” measures demonstrated high internal consistency and good model fit to a unidimensional model for both patients and parents using confirmatory factor analysis. The measures also demonstrated convergent validity with co-administered measures. This study demonstrated the validity of “providing validation” measures for parents and adult patients with vascular anomalies.

Parenting and other potential protective factors associated with polysubstance use among public school students in Lagos, Nigeria.

Substance use is a growing problem in Nigeria. The present study extended recent work documenting the importance of parenting as protective against substance use in Nigerian youth by testing a model linking parenting, additional protective factors and polysubstance use. Public school students (N = 1607; 56% female; M age = 14.88; SD = .44 years) living in the greater Lagos region participated in school-based data collection. Lifetime polysubstance use, defined as use of two or more substances including alcohol or illicit drugs, or misuse of over-the-counter medications, was reported by 5.2% of the sample. Structural equation modelling that accounted for adolescent age and sex on all constructs revealed good model fit. Positive parenting (support and solicitation) was significantly associated with higher perceived harmfulness of substance use, religiosity and positive relationships at school. Positive school relationships were associated with a decreased likelihood of polysubstance use. Multiple group analysis revealed no overall sex differences in the model paths. Strengthening parent-adolescent relationships may have a cascading effect on protective factors and subsequent substance use, and should be included in youth substance use prevention programmes.

An Indonesian-version of the short attitude toward mathematics inventory: a voice from pre-service chemistry teacher

<span lang="EN-US">This study aimed to examine the validity of the Indonesian version of the short attitude toward mathematics inventory (ATMI). The adapted inventory was also used for further analysis to explore mathematics attitude of pre-service chemistry teachers across gender. The original ATMI was translated into Bahasa and distributed to 328 participants via the online survey. After preliminary checking for multivariate outliers, all the data were used to analyze the construct validity of structural model using confirmatory factor analysis (CFA). Furthermore, multigroup analysis with structured mean modelling was conducted to explore the gender effect toward mathematics attitude. All item means, standard deviations and correlation matrix were also explored. The result found that the short form supported the four-factor solution as the original ATMI. Modification indices, standardized regression weight, and squared multiple correlations were used to determine which items to be removed or retained during analysis until standard criteria for model fit reached. This items deletion produced a shorter version of ATMI (19 items) with fairly good internal consistency, both for all items inventory (α=0.92) or for individual subscale (mean α=0.86). Moreover, the t-test on the latent mean value showed no significant difference of attitude toward mathematics between male and female.</span>

Predicting the responses of European grassland communities to climate and land cover change.

European grasslands are among the most species-rich ecosystems on small spatial scales. However, human-induced activities like land use and climate change pose significant threats to this diversity. To explore how climate and land cover change will affect biodiversity and community composition in grassland ecosystems, we conducted joint species distribution models (SDMs) on the extensive vegetation-plot database sPlotOpen to project distributions of 1178 grassland species across Europe under current conditions and three future scenarios. We further compared model accuracy and computational efficiency between joint SDMs (JSDMs) and stacked SDMs, especially for rare species. Our results show that: (i) grassland communities in the mountain ranges are expected to suffer high rates of species loss, while those in western, northern and eastern Europe will experience substantial turnover; (ii) scaling anomalies were observed in the predicted species richness, reflecting regional differences in the dominant drivers of assembly processes; (iii) JSDMs did not outperform stacked SDMs in predictive power but demonstrated superior efficiency in model fitting and predicting; and (iv) incorporating co-occurrence datasets improved the model performance in predicting the distribution of rare species. This article is part of the theme issue 'Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere'.

Examining Citizens’ Expectations and Perceptions About Service Quality in Public Sector: Adapting a Hybrid Public Service Quality Model to the Local Context

ABSTRACT The empirical study examines citizens’ expectations and perceptions about service quality in three major public institutions. The article adopts a quantitative approach. Citizens’ expectations and perceptions about service quality in the context of public institutions were examined through a questionnaire, utilizing a hybrid model of SERVQUAL with private and public service quality dimensions. The article presents the results of a quantitative study (sample of 310 citizens), distributed across three public institutions, illustrating factor, gap, paired correlation and one-way analysis of variance (ANOVA) of survey data. For factor extraction, rotation and interpretation, the Oblimin rotation technique was used, determining inter-correlation among the public service quality factors. As for ANOVA analysis, Levene’s test was used to verify the homogeneity of variance assumption (the variance in scores for each group of customers). The findings of the study suggest the re-distribution of components under the refined service quality factors. Different items of initial service quality dimensions are rotated under newly created factors. Gap analysis reveals no variations in terms of citizens’ expectations across public institutions, but suggests significant differences among public entities in regard to perceptions of services acquired. Adapted Hybrid Public Service Quality model will assist public institutions in developing and tailoring service quality management systems to citizens’ needs. This is the first attempt to carry out a quantitative approach to researching Service Quality in public institutions. The primary contribution of the study is that it has tested a hybrid model for measuring perceived public service quality, integrating service quality dimensions both from public and private sectors and proposed a refined model fit for the local context considering citizens’ characteristics and the current state of the public sector experiencing a shift toward modernization of services.

Informing Structural Assumptions for Three State Oncology Cost-Effectiveness Models through Model Efficiency and Fit.

The characteristics and relative strengths and weaknesses of partitioned survival models (PSMs) and state transition models (STMs) for three state oncology cost-effectiveness models have previously been studied. Despite clear and longstanding economic modeling guidelines, more than one structure is rarely presented, and the choice of structure appears correlated more with audience or precedent than disease, decision problem, or available data. One reason may be a lack of guidance and tools available to readily compare measures of internal validity such as the model fit and efficiency of different structures, or sensitivity of results to those choices. To address this gap, methods are presented to evaluate the fit and efficiency of three structures, with an accompanying R software package, psm3mkv. The methods are illustrated by analyzing interim and final analysis datasets of the KEYNOTE-826 randomized controlled trial. At both interim and final analyses, the STM Clock Reset structure provided the best and most efficient fit. Structural uncertainties had been reduced from interim to final analysis. Beyond measures of internal validity, guidelines highlight the importance of reflecting all available data, avoiding model selection purely on the basis of goodness of fit and strongly considering external validity. The method and software allow modelers to more easily evaluate and report model fit and efficiency, examine implicit assumptions, and reveal sensitivities to structural choices.

Bayesian cross-validation by parallel Markov chain Monte Carlo

Brute force cross-validation (CV) is a method for predictive assessment and model selection that is general and applicable to a wide range of Bayesian models. Naive or ‘brute force’ CV approaches are often too computationally costly for interactive modeling workflows, especially when inference relies on Markov chain Monte Carlo (MCMC). We propose overcoming this limitation using massively parallel MCMC. Using accelerator hardware such as graphics processor units, our approach can be about as fast (in wall clock time) as a single full-data model fit. Parallel CV is flexible because it can easily exploit a wide range data partitioning schemes, such as those designed for non-exchangeable data. It can also accommodate a range of scoring rules. We propose MCMC diagnostics, including a summary of MCMC mixing based on the popular potential scale reduction factor (R^\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\widehat{\ extrm{R}}$$\\end{document}) and MCMC effective sample size (ESS^\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\widehat{\ extrm{ESS}}$$\\end{document}) measures. We also describe a method for determining whether an R^\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\widehat{\ extrm{R}}$$\\end{document} diagnostic indicates approximate stationarity of the chains, that may be of more general interest for applications beyond parallel CV. Finally, we show that parallel CV and its diagnostics can be implemented with online algorithms, allowing parallel CV to scale up to very large blocking designs on memory-constrained computing accelerators.

Development and psychometric evaluation of the adjuvant endocrine therapy beliefs scale for breast cancer survivors.

Adjuvant endocrine therapy has a vital role in reducing breast cancer mortality. The beliefs in adjuvant endocrine therapy is a very important factor in the medication adherence of breast cancer survivors. Therefore, it is necessary to develop a standardized scale for assessment of adjuvant endocrine therapy. The purpose of this study was to identify the attributes of adjuvant endocrine therapy beliefs, and to evaluate adjuvant endocrine therapy beliefs scale psychometric properties. A hybrid model was applied to identify the concept of adjuvant endocrine therapy beliefs and measurement question were developed by the scale development process. Statistical analysis using validity analysis and Rasch analysis based on item response theory were performed. A total of 228 breast cancer survivors in South Korea participated in the study. The finally developed adjuvant endocrine therapy beliefs scale consisted of 22 items. The items extracted by 4 factors explained 59.72% of the total variance. The model fit showed an acceptable level. The adjuvant endocrine therapy beliefs scale was excellent in convergent and discriminant validity with reliability. This scale is expected to be practical and useful in identifying adjuvant endocrine therapy beliefs and developing intervention strategies to promote adjuvant endocrine therapy adherence. In addition, continuous education and support should be accompanied so that breast cancer survivors can maintain positive beliefs in adjuvant endocrine therapy adherence.

Early maladaptive schemas, distress tolerance and self-injury in Iranian adolescents: serial mediation model of transdiagnostic factors.

Non-suicidal self-injury (NSSI) is prevalent behaviour among adolescents. Although there are different etiological models of NSSI, there is a general lack of evidence-based, comprehensive and transdiagnostic models of NSSI in adolescents. The aim of this study was to investigate a model of transdiagnostic factors of NSSI in adolescents, testing a serial mediation model of the relationship between early maladaptive schemas (EMS), distress tolerance and NSSI through experiential avoidance and rumination. A community sample was identified of 1014 adolescents aged 13-17, of whom 425 had a history of NSSI. A serial mediation path analytic method was utilised to examine the relationships between NSSI and its associated functions as criterion variables, EMS and distress tolerance as predictors, experiential avoidance as the first mediator and rumination as the second mediator. The path analytic model fit indices were good (X2/d.f. = 2.25, goodness of fit index = 0.98, normed fit index = 0.97, comparative fit index = 0.98, root mean square error of approximation = 0.054, standardised root mean squared residual = 0.028). Rumination significantly mediated the relationship between schemas of 'vulnerability to harm', 'emotional deprivation', 'social isolation', 'insufficient self-control', and NSSI frequency and intrapersonal functions. In serial fashion, experiential avoidance mediated the role of rumination in the relationship between social isolation, and insufficient self-control and NSSI frequency and intrapersonal functions. All indirect effects were significant. Key indirect effects were found linking maladaptive schemas and distress tolerance to NSSI frequency, and NSSI intrapersonal functions via experiential avoidance and rumination. Thus, it is important to address these transdiagnostic factors with particular emphasis on the sequential mediating role of experiential avoidance and rumination in conceptualisation and therapeutic interventions for NSSI.

Employee learning and skilling in AI embedded organizations – predictors and outcomes

Purpose In this research article we aim to answer two research questions: - With ever increasing AI based integrations in organizations, it is imperative to understand how employees learn and adapt to these newer technologies? What is the impact of this learning and adaptation on AI-based employee productivity? Design/methodology/approach A survey-based research design has been conducted among the employees working in technology companies. Questionnaires were administered by the researchers physically using snowball based purposive sampling to reach the participants who are working in the AI driven technology companies. The data was analyzed using Structural Equation Modelling and numerous studies have previously used this approach for model fit and testing. Findings it was found that employee learning has significant positive mediational impact on the relationship between AI trust, knowledge sharing and AI skills and AI-employee collaboration. SEM results indicate that data fits the proposed model well. Practical implications findings indicate that as the trust in AI develops, employees are more interested in learning and increasing their understanding of AI driven work and increase their AI skills such as Machine learning and data analytics. To increase AI-employee collaborations and upskilling: organizations will need to foster AI training opportunities; make employees work on projects having AI based sociotechnical systems; create environment of knowledge sharing among employees on AI themes. Originality/value The use of Artificial Intelligence (AI) is ubiquitous, and more and more organizations are adopting AI in their operations which lead to massive scale changes in the functioning of organizations. These large-scale massive transformations are posing challenges and opportunities at the same time. At the same time, it created immense challenges for employees’ adjustment to the new learning and skilling requirements posed by AI (Sengupta et al., 2022). It is therefore expected that employees embrace the associated new technologies of AI such as big data analytics, Machine learning and Robotics.

Modelling the Discount Function through the Yield Curve Trajectories of the Parsimonious Continuous De Rezende Framework

This paper obtains the term structure technique to produce yield curves from Nigerian Eurobond by using the De Rezende parametric function. There does not seem to exist any empirical proof that Nigeria has constructed a functional model to construct its discount function from the yield curves. Therefore, the De Rezende parsimoniously parametric function is deeply examined to make this framework applicable in presenting yield curves for Nigerian Euro bond constructed through the associated positive forward curve and from where the discount function is generated. The forward rate should be continuous and at the same time generate a positive yield curve trajectory. The objective of this paper is (i) construct the yield curve trajectories and (ii) to construct the discount function from the yield curve (iii) to construct the in-sample prediction to achieve results in predicting coefficients for longer maturities. The data presented involves the daily closing of the Nigerian Eurobond yield covering January to December 2022, which is fitted to the observed Nigerian Eurobond yield curve to construct the yield function. The ordinary least square is applied to estimate the parameters used in computing the in-sample yield. A test of goodness of fit was conducted showing that the model fits in well to the observed data demonstrated by the model’s high R -square adjusted through the predicted yields after obtaining the decay factors.

Sustainable Employability of People with Limited Capability for Work: The Participatory Development and Validation of a Questionnaire.

Understanding sustainable employability (SE) of people with limited capability for work (LCW) due to physical or mental disability is crucial for the sustainable participation of this target group. Therefore, adequate measurement instruments for SE are needed. This study aims to validate a questionnaire to measure SE among people with LCW using a participatory approach, including person-job fit (PJ fit) and work-related sense of coherence (Work-SoC). Existing scales for the main concepts were tested and adapted for face validity via cognitive interviews (n = 6), with the involvement of a co-researcher with LCW in the research team. Next, the questionnaire was administered among people with LCW (n = 248) to assess its factor structure (Confirmatory Factor Analysis) and reliability (Cronbach's alpha). Analysis of the cognitive interviews identified problems with clarity and readability of items, instructions and response categories of used (existing) scales. The main adjustments concerned the shortening of text length, the usage of familiar language and examples, and the addition of an introduction game. Most of the adapted SE indicator scales showed an overall good fit and acceptable-to-good internal reliability. The overall SE model had an overall good fit, and excluding 'internal employability' further improved this fit. PJ fit and Work-SoC had an acceptable/good model fit and internal consistency. The participatory validation process resulted in a validated and comprehensive questionnaire to measure SE, PJ fit and Work-SoC among people with LCW, which enables research into the development of their SE. This questionnaire can be utilised to contribute to a more inclusive labour market.

The fusion point of temporal binding: Promises and perils of multisensory accounts

Performing an action to initiate a consequence in the environment triggers the perceptual illusion of temporal binding. This phenomenon entails that actions and following effects are perceived to occur closer in time than they do outside the action-effect relationship. Here we ask whether temporal binding can be explained in terms of multisensory integration, by assuming either multisensory fusion or partial integration of the two events. We gathered two datasets featuring a wide range of action-effect delays as a key factor influencing integration. We then tested the fit of a computational model for multisensory integration, the statistically optimal cue integration (SOCI) model. Indeed, qualitative aspects of the data on a group-level followed the principles of a multisensory account. By contrast, quantitative evidence from a comprehensive model evaluation indicated that temporal binding cannot be reduced to multisensory integration. Rather, multisensory integration should be seen as one of several component processes underlying temporal binding on an individual level.

Relationship between Socioeconomic Status and Pro-Environmental Behavior: The Role of Efficacy Beliefs

Efficacy beliefs are important determinants of human behavior. In the context of social cognitive theory, the perception of collective efficacy is closely related to the individual perception of self-efficacy, which is influenced by socio-structural factors such as socioeconomic status (SES). Surprisingly, the relationship between these variables has received little attention in the literature on environmental issues. Within the framework of social cognitive theory, the aim of this study was to investigate whether SES has a direct effect on pro-environmental behavior and whether it has an indirect effect via perceptions of self-efficacy and collective efficacy, in relation to climate change mitigation behavior. An online cross-sectional study was conducted using a quota sample of 1075 participants (51.9% women) aged 18–79 years. Participants reported their SES using objective and subjective measures, perceptions of their own and collective efficacy in mitigating climate change, and the frequency of their pro-environmental behaviors. Structural equation modeling revealed that the model with serial mediation effects of self-efficacy and collective efficacy between SES (both objective and subjective) and pro-environmental behaviors showed a good model fit. As expected, both objective and subjective SES had no direct effect on pro-environmental behavior. Surprisingly, neither objective nor subjective SES had an indirect effect (via efficacy beliefs) on pro-environmental behavior. However, both self-efficacy and collective efficacy were associated with pro-environmental behavior. These findings have practical implications for the development of strategies aimed at enhancing pro-environmental behavior.

A Visualization Tool to Study Dyadic Caregiving Health Profiles.

Guided by a life course perspective and fundamental cause theory, this study aims to visualize co-trajectories of health between partners and examine how changes in one spouse's cognitive status can cohesively impact the health of the other spouse along three dimensions (functional, mental, and cognitive). Drawing longitudinal data from the Health and Retirement Study 2000-2016 (N = 3582), we measure women's health profiles by functional limitation (physical health), depression (mental health), and cognitive function (cognitive health). We use multivariate linear mixed models to summarize these paths in the same visual representation. The approach provides a visualization tool that depicts data and model in the same spatial representation allowing assessment of model fit and comparison. This study advances the traditional life course studies by representing underlying processes as a multidimensional time vector of health outcomes. The described approach provides a blueprint for studying complex health profiles or trajectories.

A LIGAÇÃO ENTRE A CAPACIDADE DE INTERAÇÃO PROATIVA COM O DESEMPENHO DA EQUIPE DE TRABALHO EM HOTÉIS CINCO ESTRELAS

Objective: This research aims to use proactive interaction capability as a mediating variable for the influence of knowledge sharing on work team performance. Method: This research method was developed in a causal research design in which research hypotheses will be tested, with the aim of identifying causal relationships between variables. The population in this study were all department managers in the 5 Star hotel industry in West Java with a sample of 22 hotels. These departments include Front Office, Food and Beverage service, Food and Beverage products, Housekeeping, Accounting, HRD, Engineering, Marketing and Security. Apart from that, the hotel owner is a member of the Indonesian Hotel and Restaurant Association (PHRI) and the hotel has been operating for more than 10 (ten) years. The data source used in this research is primary data with data collected using a list of statements submitted directly to respondents. The data analysis method used in this research uses variance-based or component-based SEM structural equation modeling techniques which include several steps including preparing flow diagrams, model fit research, and structural model assessment. Results and Discussion: The results of this research show several findings, including (1) the work team efficacy variable is not able to mediate proactive interaction capability and work team performance, (2) the proactive interaction capability variable is able to mediate knowledge sharing on work team performance. Originality/Value: Proactive interaction capability in this research is a new initiative in explaining the process of how knowledge sharing can improve work team performance.

Adsorbent Biomaterials Based on Natural Clays and Orange Peel Waste for the Removal of Anionic Dyes from Water

This study demonstrates the efficient removal of Alizarin Yellow R anionic dye (AY) from aqueous solutions using green adsorbents. Natural kaolin clay (A1), acid-modified natural clay (A2), chemically treated orange peel (C1) and biochar produced by the thermal treatment of orange peel (C2) were tested for the adsorption of AY. The characteristics of the sorbents were determined by instrumental methods: SEM, EDS, FTIR, BET and TGA. The adsorption experiments were performed under different conditions, including the initial AY dye concentration, adsorbent weight, pH, temperature and contact time. The maximum adsorption capacities had values between 15.72 and 74.62 mg/g at 298 K and the optimal pH of 6.5 at initial concentrations ranging from 30 to 70 mg/L for all adsorbents. The equilibrium data were used for the adsorption isotherm models: Freundlich, Langmuir and Temkin. The Freundlich model fit best for the adsorbents A2, C1 and C2, and the Langmuir isotherm had the highest regression value for the adsorbent A1 (R2 = 0.9935). Thermodynamic parameters indicated the spontaneous and favorable adsorption process of AY. A study of the adsorption kinetics proved that they best fit the pseudo-second-order model, with the highest coefficients of determination (R2), outperforming the pseudo-first-order model. The results of this study indicate the potential for the valorization of locally available clays and orange peel waste in the purification processes of water.

Dual-time-point dynamic 68Ga-PSMA-11 PET/CT for parametric imaging generation in prostate cancer.

To investigate the optimal dual-time-point (DTP) approaches using dynamic 68Ga-PSMA-11 PET/CT imaging to generate parametric images for prostate cancer patients. Fifteen patients with prostate cancer were intravenously administered 68Ga-PSMA-11 of 181.9 ± 47.2MBq, followed by an immediate 60min dynamic PET/CT scan. List-mode data were reconstructed into 25 timeframes (6 × 10s, 8 × 30s, and 11 × 300s) and corrected for motion and partial volume effect. DTP parametric images were generated using different interval time points of 5min and 10min, with a minimum of 30min time interval. Net influx rates (Ki) were calculated through the fitting of a single irreversible two-tissue compartmental model. Intraclass correlation coefficient (ICC) values between DTP protocols and 60min Ki were obtained. Lesion-to-background ratios (LBRs) of Ki and standardized uptake value (SUV) images in each DTP protocol were determined. The DTP protocol of 5-10min with a 40-45min interval showed the highest ICC of 0.988 compared with the 60min Ki, whereas the ICC values for the intervals of 0-5min with 55-60min and 0-10min with 50-60min were 0.941. The LBRs of the 60min Ki, 5-10min with 40-45min Ki, 0-5min with 55-60min Ki, 0-10min with 50-60min Ki, SUVmean, and SUVmax images were 29.53 ± 27.33, 13.05 ± 15.28, 45.15 ± 53.11, 45.52 ± 70.31, 19.77 ± 23.43, and 25.06 ± 30.07, respectively. The 0-5min with 55-60min DTP parametric imaging exhibits a comparable Ki to 60min parametric imaging and remarkable image quality and contrast than SUV imaging, enhancing prostate cancer diagnosis while maintaining time efficiency.