Posterior Interval Research Articles

Impact of prenatal stress on offspring glucocorticoid levels: A phylogenetic meta-analysis across 14 vertebrate species

Prenatal exposure to maternal stress is commonly associated with variation in Hypothalamic Pituitary Adrenal (HPA)-axis functioning in offspring. However, the strength or consistency of this response has never been empirically evaluated across vertebrate species. Here we meta-analyzed 114 results from 39 studies across 14 vertebrate species using Bayesian phylogenetic mixed-effects models. We found a positive overall effect of prenatal stress on offspring glucocorticoids (d’ = 0.43) though the 95% Highest Posterior Density Interval overlapped with 0 (−0.16–0.95). Meta-regressions of potential moderators highlighted that phylogeny and life history variables predicted relatively little variation in effect size. Experimental studies (d’ = 0.64) produced stronger effects than observational ones (d’ = −0.01), while prenatal stress affected glucocorticoid recovery following offspring stress exposure more strongly (d’ = 0.75) than baseline levels (d’ = 0.48) or glucocorticoid peak response (d’ = 0.36). These findings are consistent with the argument that HPA-axis sensitivity to prenatal stress is evolutionarily ancient and occurs regardless of a species’ overall life history strategy. These effects may therefore be especially important for mediating intra-specific life-history variation. In addition, these findings suggest that animal models of prenatal HPA-axis programming may be appropriate for studying similar effects in humans.

Evaluation of a multiplex immunoassay for bovine respiratory syncytial virus and bovine coronavirus antibodies in bulk tank milk against two indirect ELISAs using latent class analysis

Bovine respiratory syncytial virus (BRSV) and bovine coronavirus (BCV) are responsible for respiratory disease and diarrhea in cattle worldwide. The Norwegian control program against these infections is based on herd-level diagnosis using a new multiplex immunoassay. The objective of this study was to estimate sensitivity and specificity across different cut-off values for the MVD-Enferplex BCV/BRSV multiplex, by comparing them to a commercially available ELISA, the SVANOVIR® BCV-Ab and SVANOVIR® BRSV-Ab, respectively. We analyzed bulk tank milk samples from 360 herds in a low- and 360 herds in a high-prevalence area. As none of the tests were considered perfect, estimation of test characteristics was performed using Bayesian latent class models. At the manufacturers’ recommended cut-off values, the median sensitivity for the BRSV multiplex and the BRSV ELISA was 94.4 [89.8–98.7 95% Posterior Credibility Interval (PCI)] and 99.8 [98.7–100 95% PCI], respectively. The median specificity for the BRSV multiplex was 90.6 [85.5–94.4 95% PCI], but only 57.4 [50.5–64.4 95% PCI] for the BRSV ELISA. However, increasing the cut-off of the BRSV ELISA increased specificity without compromising sensitivity. For the BCV multiplex we found that by using only one of the three antigens included in the test, the specificity increased, without concurrent loss in sensitivity. At the recommended cut-off this resulted in a sensitivity of 99.9 [99.3–100 95% PCI] and specificity of 93.7 [88.8–97.8 95% PCI] for the multiplex and a sensitivity of 99.5 [98.1–100 95% PCI] and a specificity of 99.6 [97.6–100 95% PCI] for the BCV ELISA.

Vicariance versus dispersal across Beringian land bridges to explain circumpolar distribution: A case study in plants with high dispersal potential

AbstractAimTo disentangle the importance of the Beringian land bridges during the Pliocene and Quaternary periods in order to explain the current distribution of circumpolar plants with potential for long‐distance dispersal.LocationCircumpolar (Arctic and Antarctic).MethodsWe sampled all extant species in Carex section Glareosae (26 species and 2 subspecies) and analysed 14 DNA regions, including the nrDNA regions ETS and ITS, three nuclear single‐copy genes (CATP, G3PDH and GZF), and nine cpDNA regions: 5′trnK intron, atpIH, matK, ndhJ‐trnF, psbA‐trnH, rpl32‐trnL, rps16, trnC‐ycf6 and ycf6‐psbM. After testing for outlier proportions, we used Bayesian inference, maximum likelihood and a species‐tree approach to infer phylogenetic relationships between species; divergence times were estimated using Beast2. We then performed biogeographical analyses using “BioGeoBEARS” to estimate ancestral areas by means of reticulate models. Finally, lineage through time (LTT) and diversification pattern analyses were performed using Bamm.ResultsCarex section Glareosae is a monophyletic group that diverged c. 6.56 Ma (4.54–8.51 Ma at 95% highest posterior density interval). We show that within‐area cladogenetic speciation events and anagenetic dispersal (including some vicariance events) play an important role in shaping distribution in species with potential for long‐distance dispersal. Diversification patterns show constant diversification rates over time.Main conclusionsThe Bering Strait may have played an important role in shaping the current distribution of the species in the section, facilitating dispersal between Asia and North America during glacial periods when the Beringian land bridges were open. Nevertheless, we cannot discount long‐distance dispersal as an alternative major force shaping the species distribution in the section.

A Pragmatic Approach to Statistical Testing and Estimation (PASTE)

The p-value has dominated research in education and related fields and a statistically non-significant p-value is quite commonly interpreted as ‘confirming’ the null hypothesis (H0) of ‘equivalence’. This is unfortunate, because p-values are not fit for that purpose. This paper discusses three alternatives to the traditional p-value that unfortunately have remained underused but can provide evidence in favor of ‘equivalence’ relative to ‘non-equivalence’: two one-sided tests (TOST) equivalence testing, Bayesian hypothesis testing, and information criteria. TOST equivalence testing and p-values both rely on concepts of statistical significance testing and can both be done with confidence intervals, but treat H0 and the alternative hypothesis (H1) differently. Bayesian hypothesis testing and the Bayesian credible interval aka posterior interval provide Bayesian alternatives to traditional p-values, TOST equivalence testing, and confidence intervals. However, under conditions outlined in this paper, confidence intervals and posterior intervals may yield very similar interval estimates. Moreover, Bayesian hypothesis testing and information criteria provide fairly easy to use alternatives to statistical significance testing when multiple competing models can be compared. Based on these considerations, this paper outlines a pragmatic approach to statistical testing and estimation (PASTE) for research in education and related fields. In a nutshell, PASTE states that all of the alternatives to p-values discussed in this paper are better than p-values, that confidence intervals and posterior intervals may both provide useful interval estimates, and that Bayesian hypothesis testing and information criteria should be used when the comparison of multiple models is concerned.

A Bayesian Analysis of Prenatal Maternal Factors Predicting Nonadherence to Infant HIV Medication in South Africa.

While efforts to prevent mother-to-child transmission of HIV been successful in some districts in South Africa, rates remain unacceptably high in others. This study utilized Bayesian logistic regression to examine maternal-level predictors of adherence to infant nevirapine prophylaxis, including intimate partner violence, maternal adherence, HIV serostatus disclosure reaction, recency of HIV diagnosis, and depression. Women (N=303) were assessed during pregnancy and 6weeks postpartum. Maternal adherence to antiretroviral therapy during pregnancy predicted an 80% reduction in the odds of infant nonadherence [OR 0.20, 95% posterior credible interval (.11, .38)], and maternal prenatal depression predicted an increase [OR 1.04, 95% PCI (1.01, 1.08)]. Results suggest that in rural South Africa, failure to provide medication to infants may arise from shared risk factors with maternal nonadherence. Intervening to increase maternal adherence and reduce depression may improve adherence to infant prophylaxis and ultimately reduce vertical transmission rates.

Ambient carbon monoxide and cardiovascular mortality: a nationwide time-series analysis in 272 cities in China

Evidence of the acute health effects of ambient carbon monoxide air pollution in developing countries is scarce and mixed. We aimed to evaluate short-term associations between carbon monoxide and daily cardiovascular disease mortality in China. We did a nationwide time-series analysis in 272 major cities in China from January, 2013, to December, 2015. We extracted daily cardiovascular disease mortality data from China's Disease Surveillance Points system. Data on daily carbon monoxide concentrations for each city were obtained from the National Urban Air Quality Real-time Publishing Platform. City-specific associations between carbon monoxide concentrations and daily mortality from cardiovascular disease, coronary heart disease, and stroke were estimated with over-dispersed generalised linear models. Bayesian hierarchical models were used to obtain national and regional average associations. Exposure-response association curves and potential effect modifiers were evaluated. Two-pollutant models were fit to evaluate the robustness of the effects of carbon monoxide on cardiovascular mortality. The average annual mean carbon monoxide concentration in these cities from 2013 to 2015 was 1·20 mg/m3, ranging from 0·43 mg/m3 to 2·45 mg/m3. For a 1 mg/m3 increase in average carbon monoxide concentrations on the present day and previous day (lag 0-1), we observed significant increments in mortality of 1·12% (95% posterior interval [PI] 0·42-1·83) from cardiovascular disease, 1·75% (0·85-2·66) from coronary heart disease, and 0·88% (0·07-1·69) from stroke. These associations did not vary substantially by city, region, and demographic characteristics (age, sex, and level of education), and the associations for cardiovascular disease and coronary heart disease were robust to the adjustment of criteria co-pollutants. We did not find a threshold below which carbon monoxide exposure had no effect on cardiovascular disease mortality. This analysis is, to our knowledge, the largest study done in a developing country, and provides robust evidence of the association between short-term exposure to ambient carbon monoxide and increased cardiovascular disease mortality, especially coronary heart disease mortality. Public Welfare Research Program.

Evaluation of three serological tests for diagnosis of bovine brucellosis in smallholder farms in Pakistan by estimating sensitivity and specificity using Bayesian latent class analysis

The present study aimed to estimate the herd-level sensitivity (Se) and specificity (Sp) of three commonly used serological tests in naturally-infected cattle and buffalo in smallholder farms in Pakistan. Between February and June 2015, a cross-sectional study was carried out in five districts of Punjab (Kasur, Okara, Pakpattan, Jhelum, and Bhakkar) and two districts of Sindh (Badin and Thatta). Serum samples from mixed farms of cattle (n=441) and buffalo (n=621) were collected and tested using the Rose Bengal test (RBT), indirect ELISA (I-ELISA) and competitive ELISA (C-ELISA). A Bayesian latent class analysis (LCA) approach was used to estimate the Se and Sp of these three serological tests and the true herd-level prevalence in each district. The model was fitted under the assumption of conditional independence between three tests and also conditional dependence by including covariances between the two ELISAs. In addition, the model was fitted using three different shapes of beta distributions to incorporate prior information in the model. The test with the highest Se was the C-ELISA, with a range from 76.3% (95% PCI (Posterior Credibility Interval), 62.6–88.2%) to 81.4% (95% PCI, 68.2–92.8%). The RBT was found to have the highest Sp (99.1–99.4%) of the tests. The highest estimated herd-level prevalence, 45% (95% PCI, 32–59%), was found in Jhelum district and the lowest in Thatta district, 1.1% (95% PCI 0.04–6.0%). The results of this study identified some discrepancy between the published literature on the level of Se of these tests, especially for RBT. It appears that RBT has lower Se and higher Sp when used in the field conditions of the present study. Consequently, it is recommended that none of the evaluated tests should be performed in isolation for the diagnosis of bovine brucellosis in the field conditions of Pakistan, but the use of tests in combination, with RBT and C-ELISA used in parallel returning optimal Se and Sp, is warranted.

Ambient Ozone Pollution and Daily Mortality: A Nationwide Study in 272 Chinese Cities.

Background:Few large multicity studies have been conducted in developing countries to address the acute health effects of atmospheric ozone pollution.Objective:We explored the associations between ozone and daily cause-specific mortality in China.Methods:We performed a nationwide time-series analysis in 272 representative Chinese cities between 2013 and 2015. We used distributed lag models and over-dispersed generalized linear models to estimate the cumulative effects of ozone (lagged over 0–3 d) on mortality in each city, and we used hierarchical Bayesian models to combine the city-specific estimates. Regional, seasonal, and demographic heterogeneity were evaluated by meta-regression.Results:At the national-average level, a increase in 8-h maximum ozone concentration was associated with 0.24% [95% posterior interval (PI): 0.13%, 0.35%], 0.27% (95% PI: 0.10%, 0.44%), 0.60% (95% PI: 0.08%, 1.11%), 0.24% (95% PI: 0.02%, 0.46%), and 0.29% (95% PI: 0.07%, 0.50%) higher daily mortality from all nonaccidental causes, cardiovascular diseases, hypertension, coronary diseases, and stroke, respectively. Associations between ozone and daily mortality due to respiratory and chronic obstructive pulmonary disease specifically were positive but imprecise and nonsignificant. There were no statistically significant differences in associations between ozone and nonaccidental mortality according to region, season, age, sex, or educational attainment.Conclusions:Our findings provide robust evidence of higher nonaccidental and cardiovascular mortality in association with short-term exposure to ambient ozone in China. https://doi.org/10.1289/EHP1849

Bayesian Credible Intervals for Maize Grain Yields of the Maintenance Varieties Evaluated in Sudan

Improved of maintenance crop varieties developed at agricultural research corporation, Wad median, Sudan is intended for seed foundation which is recently established. This study was undertaken to establish statistical investigation using Bayesian estimation for credible interval or posterior interval as a Bayesian strategy for a maintenance variety. Data on grain yield (kg/ha) on a maize crop variety were used. Bayesian posterior information can be annoying to investigate but are important in maintenance varieties that foundational claims are used to make general recommendations for practice. Half normal informative priors set were used. The heritability of yield (varieties)) was (h = 0.75). Predicted posterior means of varieties were shown with a Bayesian interval for scientific inference in the maintenance maize grain yield. Bayesian approach is useful for reducing uncertainty on decisions based on economic evaluation of new maize varieties in Sudan, the use of credible intervals for grain yield allow for early decisions.Int. J. Appl. Sci. Biotechnol. Vol 5(3): 390-396

Responses of Sunda clouded leopardNeofelis diardipopulation density to anthropogenic disturbance: refining estimates of its conservation status in Sabah

AbstractExtensive areas of tropical forests have been, and continue to be, disturbed as a result of selective timber extraction. Although such anthropogenic disturbance typically results in the loss of biodiversity, many species persist, and their conservation in production landscapes could be enhanced by a greater understanding of how biodiversity responds to forest management practices. We conducted intensive camera-trap surveys of eight protected forest areas in Sabah, Malaysian Borneo, and developed estimates of Sunda clouded leopardNeofelis diardipopulation density from spatially explicit capture–recapture analyses of detection data to investigate how the species’ abundance varies across the landscape and in response to anthropogenic disturbance. Estimates of population density from six forest areas were 1.39–3.10 individuals per 100 km2. Our study provides the first evidence that the population density of the Sunda clouded leopard is negatively affected by hunting pressure and forest fragmentation, and that among selectively logged forests, time since logging is positively associated with abundance. We argue that these negative anthropogenic impacts could be mitigated with improved logging practices, such as reducing the access of poachers by effective gating and destruction of road access points, and by the deployment of anti-poaching patrols. By calculating a weighted mean population density estimate from estimates developed here and from the literature, and by extrapolating this value to an estimate of current available habitat, we estimate there are 754 (95% posterior interval 325–1,337) Sunda clouded leopards in Sabah.

Stochastic Efficiency of Bayesian Markov Chain Monte Carlo in Spatial Econometric Models: An Empirical Comparison of Exact Sampling Methods

Spatial econometric specifications pose unique computational challenges to Bayesian analysis, making it difficult to estimate models efficiently. In the literature, the main focus has been on extending Bayesian analysis to increasingly complex spatial models. The stochastic efficiency of commonly used Markov Chain Monte Carlo (MCMC) samplers has received less attention by comparison. Specifically, Bayesian methods to analyze effective sample size and samplers that provide large effective size have not been thoroughly considered in the literature. Thus, we compare three MCMC techniques: the familiar Metropolis‐within‐Gibbs sampling, Slice‐within‐Gibbs sampling, and Hamiltonian Monte Carlo. The latter two methods, while common in other domains, are not as widely encountered in Bayesian spatial econometrics. We assess these methods across four different scenarios in which we estimate the spatial autoregressive parameter in a mixed regressive, spatial autoregressive specification (or, spatial lag model). We find that off‐the‐shelf implementations of the newer high‐yield simulation techniques require significant adaptation to be viable. We further find that the effective sizes are often significantly smaller than nominal sizes. In addition, we find that stopping simulation early may understate posterior credible interval widths when effective sample size is small. More broadly, we suggest that sample information and stopping rules deserve more attention in both applied and basic Bayesian spatial econometric research.

Effectiveness of online tailored advice to prevent running-related injuries and promote preventive behaviour in Dutch trail runners: a pragmatic randomised controlled trial

BackgroundTrail running is popular worldwide, but there is no preventive intervention for running-related injury (RRI).AimTo evaluate the effectiveness of adding online tailored advice (TrailS6) to general advice on (1) the...

Development and standardization of an in-house indirect ELISA for detection of duck antibody to fowl cholera

Serological tests, such as agglutination and indirect hemagglutination assay (IHA), have been used to identify antibodies against Pasteurella multocida in poultry sera, but none are highly sensitive. An enzyme-linked immunosorbent assays (ELISA) has been used with varying degrees of success in attempts to monitor seroconversion in vaccinated poultry, but are not suitable for diagnosis. Commercial ELISA kits are available for chickens and turkeys, but not for ducks. The present study reports development and standardization of an in-house indirect ELISA for detection of duck antibody to fowl cholera. The characteristics of ELISA and IHA were analyzed using a one population Bayesian model assuming conditional dependence between the two diagnostic tests. An in-house indirect ELISA was developed using a heat extract antigen of P. multocida strain X-73 as a coating antigen and horseradish peroxidase conjugated goat anti-duck IgG antibody (dIgG-HRP). The checkerboard titration method was done using sera from ducks immunized with P. multocida bacterin as positive sera and 1day old duckling sera as negative sera. The heat extract antigen at 1μg/ml, sample serum at a dilution of 1:100, and dIgG-HRP 1:2000 were optimal concentrations for the assay. The cut-off value was 0.200. Of the duck sera, 89.05% (244/274) were considered seropositive by ELISA. Estimates for sensitivity and specificity of ELISA were higher than prior values with medians of 94.7% [95% posterior probability interval (PPI)=89.6–98.2%] and 87.2% (PPI=68.2–98.3%). Estimates for sensitivity of IHA were lower than prior values (median=97.6, PPI=93.2–99.7%) while the specificity was close to the prior value (median=76.5, PPI=65.8–85.4%). This finding suggests that an in-house indirect ELISA can be used to detect duck antibody to fowl cholera.

Statistical inference for the parameter of Lindley distribution based on fuzzy data

In many practical situations, we face data which are not only random but vague as well. To deal with these two types of uncertainties, it is necessary to incorporate fuzzy concept into statistical technique. In this paper, we investigate the maximum likelihood estimation and Bayesian estimation for Lindley distribution when the available observations are reported in the form of fuzzy data. We employ the EM algorithm to determine the maximum likelihood estimate (MLE) of the parameter and construct approximate confidence interval by using the asymptotic normality of the MLE. In the Bayesian setting, we use an approximation based on the Laplace approximation as well as a Markov Chain Monte Carlo technique to compute the Bayes estimate of the parameter. In addition, the highest posterior density credible interval of the unknown parameter is obtained. Extensive simulations are performed to compare the performances of the different proposed methods.

Simple, scalable and accurate posterior interval estimation

Summary Standard posterior sampling algorithms, such as Markov chain Monte Carlo procedures, face major challenges in scaling up to massive datasets. We propose a simple and general posterior interval estimation algorithm to rapidly and accurately estimate quantiles of the posterior distributions for one-dimensional functionals. Our algorithm runs Markov chain Monte Carlo in parallel for subsets of the data, and then averages quantiles estimated from each subset. We provide strong theoretical guarantees and show that the credible intervals from our algorithm asymptotically approximate those from the full posterior in the leading parametric order. Our algorithm has a better balance of accuracy and efficiency than its competitors across a variety of simulations and a real-data example.

Whole-Genome Sequencing Reveals the Contribution of Long-Term Carriers in Staphylococcus aureus Outbreak Investigation.

ABSTRACTWhole-genome sequencing (WGS) makes it possible to determine the relatedness of bacterial isolates at a high resolution, thereby helping to characterize outbreaks. However, for Staphylococcus aureus, the accumulation of within-host diversity during carriage might limit the interpretation of sequencing data. In this study, we hypothesized the converse, namely, that within-host diversity can in fact be exploited to reveal the involvement of long-term carriers (LTCs) in outbreaks. We analyzed WGS data from 20 historical outbreaks and applied phylogenetic methods to assess genetic relatedness and to estimate the time to most recent common ancestor (TMRCA). The findings were compared with the routine investigation results and epidemiological evidence. Outbreaks with epidemiological evidence for an LTC source had a mean estimated TMRCA (adjusted for outbreak duration) of 243 days (95% highest posterior density interval [HPD], 143 to 343 days) compared with 55 days (95% HPD, 28 to 81 days) for outbreaks lacking epidemiological evidence for an LTC (P = 0.004). A threshold of 156 days predicted LTC involvement with a sensitivity of 0.875 and a specificity of 1. We also found 6/20 outbreaks included isolates with differing antimicrobial susceptibility profiles; however, these had only modestly increased pairwise diversity (mean 17.5 single nucleotide variants [SNVs] [95% confidence interval {CI}, 17.3 to 17.8]) compared with isolates with identical antibiograms (12.7 SNVs [95% CI, 12.5 to 12.8]) (P < 0.0001). Additionally, for 2 outbreaks, WGS identified 1 or more isolates that were genetically distinct despite having the outbreak pulsed-field gel electrophoresis (PFGE) pulsotype. The duration-adjusted TMRCA allowed the involvement of LTCs in outbreaks to be identified and could be used to decide whether screening for long-term carriage (e.g., in health care workers) is warranted. Requiring identical antibiograms to trigger investigation could miss important contributors to outbreaks.

New York Heart Association class and the survival benefit from primary prevention implantable cardioverter defibrillators: A pooled analysis of 4 randomized controlled trials

Primary prevention implantable cardioverter defibrillator (ICD) reduce all-cause mortality by reducing sudden cardiac death. There are conflicting data regarding whether patients with more advanced heart failure derive ICD benefit owing to the competing risk of nonsudden death. We performed a patient-level meta-analysis of New York Heart Association (NYHA) class II/III heart failure patients (left ventricular ejection fraction ≤35%) from 4 primary prevention ICD trials (MADIT-I, MADIT-II, DEFINITE, SCD-HeFT). Bayesian-Weibull survival regression models were used to assess the impact of NYHA class on the relationship between ICD use and mortality. Of the 2,763 patients who met study criteria, 68% (n=1,867) were NYHA II and 52% (n=1,435) were randomized to an ICD. In a multivariable model including all study patients, the ICD reduced mortality (hazard ratio [HR] 0.65, 95% posterior credibility interval [PCI]) 0.40-0.99). The interaction between NYHA class and the ICD on mortality was significant (posterior probability of no interaction=.036). In models including an interaction term for the NYHA class and ICD, the ICD reduced mortality among NYHA class II patients (HR 0.55, PCI 0.35-0.85), and the point estimate suggested reduced mortality in NYHA class III patients (HR 0.76, PCI 0.48-1.24), although this was not statistically significant. Primary prevention ICDs reduce mortality in NYHA class II patients and trend toward reducing mortality in the heterogeneous group of NYHA class III patients. Improved risk stratification tools are required to guide patient selection and shared decision making among NYHA class III primary prevention ICD candidates.

Hybrid Fuzzy Estimation of System Reliability for Multi-State System

This article is purpose a hybrid estimation of the fuzzy system reliability for the Non-repairable multi-state series-parallel system (NMSS). Considering the fuzzy parameter of NMSS are prior fuzzy parameters. Then the posterior fuzzy parameters of NMSS are constructed by fuzzy Bayesian point estimate of fuzzy system reliability. Moreover, an approach to construct interval estimation of the fuzzy system reliability of NMSS will be used in estimation of the prior fuzzy confidence interval and posterior fuzzy confidence interval of fuzzy system reliability. Finally, the coverage probability and the expected length that it is used to interpret the efficiency of both fuzzy confidence intervals are presented.

Exploration on the risk factors of pulmonary tuberculosis incidence in Wenchuan earthquake-stricken area

To explore the risk factors of pulmonary tuberculosis incidence in Wenchuan earthquake-stricken area during a nine-year period of time. The incidence and socioeconomic indicators in the 181 counties of Sichuan province from 2004 to 2012 were collected, multilevel extra-Poisson model was performed for variable screening, and Bayesian spatiotemporal models were fitted. The morbidity showed a downward time trend from 2004 to 2012. The spatiotemporal interaction model was applied with the smallest deviance information criterion. The risk factors included: county latitude (0.949, 95%CI 0.765 to 1.098), float proportion (0.368, 95%CI 0.354 to 0.380), per capita GDP (-0.225, 95%CI -0.235 to -0.216), population density (0.072, 95%CI 0.041 to 0.105), and minority inhabited area (0.302, 95%CI 0.241 to 0.372). The variation of posterior median and Bayesian credibility interval was small, and the spatiotemporal patterns were similar among different periods. The incidence presented a smooth curve without bursting after the earthquake during 2004 to 2012, and with a tendency of decreasing from north to south in Sichuan province; PTB countermeasures should be focused on the migrating population and in the minority inhabited and economic underdeveloped regions. Geographical adjacent structure was an important factor and regional collaborative prevention and control should be strengthened.

Evaluating Model Fit in Bayesian Confirmatory Factor Analysis With Large Samples: Simulation Study Introducing the BRMSEA.

Bayesian confirmatory factor analysis (CFA) offers an alternative to frequentist CFA based on, for example, maximum likelihood estimation for the assessment of reliability and validity of educational and psychological measures. For increasing sample sizes, however, the applicability of current fit statistics evaluating model fit within Bayesian CFA is limited. We propose, therefore, a Bayesian variant of the root mean square error of approximation (RMSEA), the BRMSEA. A simulation study was performed with variations in model misspecification, factor loading magnitude, number of indicators, number of factors, and sample size. This showed that the 90% posterior probability interval of the BRMSEA is valid for evaluating model fit in large samples (N≥ 1,000), using cutoff values for the lower (<.05) and upper limit (<.08) as guideline. An empirical illustration further shows the advantage of the BRMSEA in large sample Bayesian CFA models. In conclusion, it can be stated that the BRMSEA is well suited to evaluate model fit in large sample Bayesian CFA models by taking sample size and model complexity into account.