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Comparing statistical analyses to estimate thresholds in ecotoxicology.

ABSTRACT: Different methods are used in ecotoxicology to estimate thresholds in survival data. This paper uses Monte Carlo simulations to evaluate the accuracy of three methods (maximum likelihood (MLE) and Markov Chain Monte Carlo estimates (Bayesian) of the no-effect concentration (NEC) model and Piecewise regression) in estimating true and apparent thresholds in survival experiments with datasets having different slopes, background mortalities, and experimental designs. Datasets were generated with models that include a threshold parameter (NEC) or not (log-logistic). Accuracy was estimated using root-mean square errors (RMSEs), and RMSE ratios were used to estimate the relative improvement in accuracy by each design and method. All methods had poor performances in shallow and intermediate curves, and accuracy increased with the slope of the curve. The EC5 was generally the most accurate method to estimate true and apparent thresholds, except for steep curves with a true threshold. In that case, the EC5 underestimated the threshold, and MLE and Bayesian estimates were more accurate. In most cases, information criteria weights did not provide strong evidence in support of the true model, suggesting that identifying the true model is a difficult task. Piecewise regression was the only method where the information criteria weights had high support for the threshold model; however, the rate of spurious threshold model selection was also high. Even though thresholds are an attractive concept from a regulatory and practical point of view, threshold estimates, under the experimental conditions evaluated in this work, should be carefully used in survival analysis or when there are any biological reasons to support the existence of a threshold.

SUBMITTER: Krull M

PROVIDER: S-EPMC7141675 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Comparing statistical analyses to estimate thresholds in ecotoxicology.

Krull Marcos M

PloS one 20200408 4

Different methods are used in ecotoxicology to estimate thresholds in survival data. This paper uses Monte Carlo simulations to evaluate the accuracy of three methods (maximum likelihood (MLE) and Markov Chain Monte Carlo estimates (Bayesian) of the no-effect concentration (NEC) model and Piecewise regression) in estimating true and apparent thresholds in survival experiments with datasets having different slopes, background mortalities, and experimental designs. Datasets were generated with mod ...[more]

PMID: 32267904

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Project description:BackgroundThere are no overviews of systematic reviews investigating haemoglobin thresholds for transfusion. This is important as the literature on transfusion thresholds has grown considerably in recent years. Our aim was to synthesise evidence from systematic reviews and meta-analyses of the effects of restrictive and liberal transfusion strategies on mortality.MethodsThis was a systematic review of systematic reviews (overview). We searched MEDLINE, Embase, Web of Science Core Collection, PubMed, Google Scholar, and the Joanna Briggs Institute EBP Database, from 2008 to 2018. We included systematic reviews and meta-analyses of randomised controlled trials comparing mortality in patients assigned to red cell transfusion strategies based on haemoglobin thresholds. Two independent reviewers extracted data and assessed methodological quality. We assessed the methodological quality of included reviews using AMSTAR 2 and the quality of evidence pooled using an algorithm to assign GRADE levels.ResultsWe included 19 systematic reviews reporting 33 meta-analyses of mortality outcomes from 53 unique randomised controlled trials. Of the 33 meta-analyses, one was graded as high quality, 15 were moderate, and 17 were low. Of the meta-analyses presenting high- to moderate-quality evidence, 12 (75.0%) reported no statistically significant difference in mortality between restrictive and liberal transfusion groups and four (25.0%) reported significantly lower mortality for patients assigned to a restrictive transfusion strategy. We found few systematic reviews addressed clinical differences between included studies: variation was observed in haemoglobin threshold concentrations, the absolute between group difference in haemoglobin threshold concentration, time to randomisation (resulting in transfusions administered prior to randomisation), and transfusion dosing regimens.ConclusionsMeta-analyses graded as high to moderate quality indicate that in most patient populations no difference in mortality exists between patients assigned to a restrictive or liberal transfusion strategy.Trial registrationPROSPERO CRD42019120503.

Project description:ObjectivesTimely assessments are critical to providing early intervention and better hearing and spoken language outcomes for children with hearing loss. To facilitate faster diagnostic hearing assessments in infants, the authors developed the parallel auditory brainstem response (pABR), which presents randomly timed trains of tone pips at five frequencies to each ear simultaneously. The pABR yields high-quality waveforms that are similar to the standard, single-frequency serial ABR but in a fraction of the recording time. While well-documented for standard ABRs, it is yet unknown how presentation rate and level interact to affect responses collected in parallel. Furthermore, the stimuli are yet to be calibrated to perceptual thresholds. Therefore, this study aimed to determine the optimal range of parameters for the pABR and to establish the normative stimulus level correction values for the ABR stimuli.DesignTwo experiments were completed, each with a group of 20 adults (18-35 years old) with normal-hearing thresholds (≤20 dB HL) from 250 to 8000 Hz. First, pABR electroencephalographic (EEG) responses were recorded for six stimulation rates and two intensities. The changes in component wave V amplitude and latency were analyzed, as well as the time required for all responses to reach a criterion signal-to-noise ratio of 0 dB. Second, behavioral thresholds were measured for pure tones and for the pABR stimuli at each rate to determine the correction factors that relate the stimulus level in dB peSPL to perceptual thresholds in dB nHL.ResultsThe pABR showed some adaptation with increased stimulation rate. A wide range of rates yielded robust responses in under 15 minutes, but 40 Hz was the optimal singular presentation rate. Extending the analysis window to include later components of the response offered further time-saving advantages for the temporally broader responses to low-frequency tone pips. The perceptual thresholds to pABR stimuli changed subtly with rate, giving a relatively similar set of correction factors to convert the level of the pABR stimuli from dB peSPL to dB nHL.ConclusionsThe optimal stimulation rate for the pABR is 40 Hz but using multiple rates may prove useful. Perceptual thresholds that subtly change across rate allow for a testing paradigm that easily transitions between rates, which may be useful for quickly estimating thresholds for different configurations of hearing loss. These optimized parameters facilitate expediency and effectiveness of the pABR to estimate hearing thresholds in a clinical setting.

Project description:PurposeThe purpose of this tutorial is to provide visual scientists with various approaches for comparing two or more groups of data using parametric statistical tests, which require that the distribution of data within each group is normal (Gaussian). Non-parametric tests are used for inference when the sample data are not normally distributed or the sample is too small to assess its true distribution.MethodsMethods are reviewed using retinal thickness, as measured by optical coherence tomography (OCT), as an example for comparing two or more group means. The following parametric statistical approaches are presented for different situations: two-sample t-test, Analysis of Variance (ANOVA), paired t-test, and the analysis of repeated measures data using a linear mixed-effects model approach.ResultsAnalyzing differences between means using various approaches is demonstrated, and follow-up procedures to analyze pairwise differences between means when there are more than two comparison groups are discussed. The assumption of equal variance between groups and methods to test for equal variances are examined. Examples of repeated measures analysis for right and left eyes on subjects, across spatial segments within the same eye (e.g. quadrants of each retina), and over time are given.ConclusionsThis tutorial outlines parametric inference tests for comparing means of two or more groups and discusses how to interpret the output from statistical software packages. Critical assumptions made by the tests and ways of checking these assumptions are discussed. Efficient study designs increase the likelihood of detecting differences between groups if such differences exist. Situations commonly encountered by vision scientists involve repeated measures from the same subject over time, measurements on both right and left eyes from the same subject, and measurements from different locations within the same eye. Repeated measurements are usually correlated, and the statistical analysis needs to account for the correlation. Doing this the right way helps to ensure rigor so that the results can be repeated and validated.

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Comparing statistical analyses to estimate thresholds in ecotoxicology.

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Comparing statistical analyses to estimate thresholds in ecotoxicology.

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