Four simple ways to increase power without increasing the sample size

Advocating for Generalizability: Accepting Inherent Variability in Translation of Animal Research Outcomes

Advancing scientific discovery requires investigators to embrace research practices that increase transparency and disclosure about materials, methods, and outcomes. Several research advocacy and funding organizations have produced guidelines and recommended practices to enhance reproducibility through detailed and rigorous research approaches; however, confusion around vocabulary terms and a lack of adoption of suggested practices have stymied successful implementation. Although reproducibility of research findings cannot be guaranteed due to extensive inherent variables in attempts at experimental repetition, the scientific community can advocate for generalizability in the application of data outcomes to ensure a broad and effective impact on the comparison of animals to translation within human research. This report reviews suggestions, based upon work with National Institutes of Health advisory groups, for improving rigor and transparency in animal research through aspects of experimental design, statistical assessment, and reporting factors to advocate for generalizability in the application of comparative outcomes between animals and humans.

Samples in many cell-based experiments are matched/paired but taking this into account does not always increase power of statistical tests for differences in means

Power of statistical tests for differences in means is the probability of obtaining a statistically significant p value when means differ. When samples in experimental replicates come from a single cell culture, they are matched or paired because they share between-trials biological variability. This can cause positive correlation between values from conditions in a replicate. Correlation can also be caused in otherwise independent samples by shared technical variability. However, correlation is reduced by noise that affects samples individually. I investigated how to maximize power in experiments with two conditions over a range of correlations. Normalizing data to control increases the rate of false positives, if Student's t test is used. Paired t tests, theoretically the correct test for matched samples, have higher power than Student's t test when correlation is high, but lower power when correlation is low. Testing correlation to select a test for differences in mean can affect the subsequent rate of false positives. Ultimately, components of experimental variability must be considered to choose the most powerful two sample test for differences in mean. This contrasts with experiments with more than two conditions, where random-block ANOVA, a matched samples test, can be used as a default.

A new approach to making scientific research more efficient - rethinking sustainability

As interest in sustainability grows, many researchers raise questions about changing scientific practices. To enable effective change, we reconceptualize sustainability as an approach that optimizes the efficiency of procedures, thereby benefiting scientists and minimizing environmental footprints. Since the implementation of sustainable approaches can be challenging, we describe the 6R concept as a framework to arrive at actionable steps.

The effectiveness of treatment with probiotics in Helicobacter pylori eradication: results from an umbrella meta-analysis on meta-analyses of randomized controlled trials

Background and aims: The purpose of this umbrella meta-analysis was to quantitatively summarize meta-analyses of randomized controlled trial (RCT) studies regarding the effects of probiotic supplementation on Helicobacter pylori (H. pylori) eradication. Methods: A thorough search of the electronic databases including PubMed, Web of Science, Embase, Scopus, and Google Scholar was carried out from the inception up to May 2022. For the evaluation of overall effect sizes, the pooled relative risk (RR) or odds ratio (OR) and their corresponding 95% confidence intervals (CI) were calculated. The random-effects model was used for the meta-analysis. Results: Overall, 18 eligible studies (47 278 participants in total) were included in the study. The findings revealed that probiotics have a beneficial impact on H. pylori eradication (pooled ESRR: 1.13; 95% CI: 1.11, 1.14, p < 0.01, and ESOR = 1.86, 95% CI: 1.70, 2.03, p < 0.01). Greater effects on H. pylori eradication were observed when higher doses (>10 × 1010 CFU) and mixed strains were supplemented. Conclusion: The present umbrella meta-analysis suggests that supplementation with probiotics may be considered as an efficient approach to ameliorate H. pylori complications, particularly probiotics with higher CFUs and mixed strains.

The Relation between Patient-Centered Care and Quality of Life in Women with Endometriosis

OBJECTIVE

The objective of this study was to examine the hypothesis that experiences with patient-centered endometriosis care are related to the endometriosis-specific quality of life dimensions "emotional well-being" and "social support."

DESIGN

A secondary regression analysis of two cross-sectional studies was conducted. Participants/Materials: In total, data from 300 women were eligible for analysis. The participating women all had surgically proven endometriosis.

SETTING

The study was conducted in one secondary and two tertiary endometriosis clinics in the Netherlands. Questionnaires were disseminated between 2011 and 2016.

METHODS

Both included studies investigated patient-centeredness of endometriosis care and endometriosis-specific quality of life using, respectively, the ENDOCARE questionnaire (ECQ) and the Endometriosis Health Profile 30 (EHP-30). To increase power, the regression analysis focused on the previously found relation between the ten dimensions of the ECQ and the EHP-30 domains "emotional well-being" and "social support" rather than all five EHP-30 domains. After the Bonferroni correction to limit type 1 errors, the adjusted p value was 0.003 (0.05/20).

RESULTS

The participating women had a mean age of 35.7 years and had predominantly been diagnosed with moderate to severe endometriosis. None of the relations between patient-centered endometriosis care and the EHP-30 domain "emotional well-being" were significant. Three dimensions of patient-centered endometriosis care proved to be significantly related to the EHP-30 domain "social support": "information, communication, and education" (p < 0.001, beta = 0.436), "coordination and integration of care" (p = 0.001, beta = 0.307), and "emotional support and alleviation of fear and anxiety" (p = 0.002, beta = 0.259).

LIMITATIONS

This cross-sectional study identified relations rather than proving causality between experiencing less patient-centeredness of care and having lower quality of life. Nevertheless, it is very tangible that some causality exists, either directly or indirectly (e.g., through empowerment) and that by improving patient-centeredness, quality of life might be improved as well.

CONCLUSION

"Information, communication, and education"; "coordination and integration of care"; and "emotional support and alleviation of fear and anxiety" as dimensions of patient-centered endometriosis care are related to the quality of life domain "social support" of women with endometriosis. Improving the patient-centeredness of endometriosis care was already considered an important goal, but even more so given its relation with women's quality of life, which is increasingly considered the ultimate measure of health care quality. Quality improvement projects focusing on "information, communication, and education" are expected to impact women's quality of life the most.

Common and rare variant associations with latent traits underlying depression, bipolar disorder, and schizophrenia

Genetic studies in psychiatry have primarily focused on the effects of common genetic variants, but few have investigated the role of rare genetic variants, particularly for major depression. In order to explore the role of rare variants in the gap between estimates of single nucleotide polymorphism (SNP) heritability and twin study heritability, we examined the contribution of common and rare genetic variants to latent traits underlying psychiatric disorders using high-quality imputed genotype data from the UK Biobank. Using a pre-registered analysis, we used items from the UK Biobank Mental Health Questionnaire relevant to three psychiatric disorders: major depression (N = 134,463), bipolar disorder (N = 117,376) and schizophrenia (N = 130,013) and identified a general hierarchical factor for each that described participants' responses. We calculated participants' scores on these latent traits and conducted single-variant genetic association testing (MAF > 0.05%), gene-based burden testing and pathway association testing associations with these latent traits. We tested for enrichment of rare variants (MAF 0.05-1%) in genes that had been previously identified by common variant genome-wide association studies, and genes previously associated with Mendelian disorders having relevant symptoms. We found moderate genetic correlations between the latent traits in our study and case-control phenotypes in previous genome-wide association studies, and identified one common genetic variant (rs72657988, minor allele frequency = 8.23%, p = 1.01 × 10^-9) associated with the general factor of schizophrenia, but no other single variants, genes or pathways passed significance thresholds in this analysis, and we did not find enrichment in previously identified genes.

Recommendations to improve use and reporting of statistics in animal experiments

Flaws in experimental statistics are a major contributor to the poor reproducibility of animal experiments. Informed decisions about whether conclusions are justified requires clear reporting of experimental data and the statistical methods used to analyse them. When data are misinterpreted, manipulated or concealed to generate publications, it creates an illusion that chance observations are robust data which confirm the hypotheses presented. Attempts to reproduce and advance such observations can propagate large areas of irreproducible science. This hinders scientific progress, erodes public support for research, damages reputations and wastes resources. This review analyses and explains recommendations to improve use and reporting of statistics in animal experiments.

Tips and traps for behavioural animal experimentation

Behavioural animal experimentation is an inseparable part of research trying to understand the biological underpinnings of human behaviour, diseases and disorders. Working with animals comes with great responsibility to achieve reliable and reproducible results of highest scientific quality. In a simple step-by-step fashion, we highlight some common issues that may occur along the path to conducting behavioural animal experimentations and posit some solutions and grounds to ensure the excellence of work done in this research area while aspiring to improve conditions for laboratory animals. It entails topics of study design, animal and experimenter welfare, experimental considerations and frequentist biostatistics. At the end, we direct to some guidelines and manuals that may prove valuable to researchers in this field. Our ten simple tips and traps are meant for students who are learning about important concepts for the first time; graduates whose statistics training all too often has neglected the concept of power in experimental design; and researches who would like a light-hearted refresher on these topics. With this perspective, we hope that you will avoid falling into traps and find answers to what you always wanted to know about conducting behavioural animal experimentation.

Science Forum: How failure to falsify in high-volume science contributes to the replication crisis

The number of scientific papers published every year continues to increase, but scientific knowledge is not progressing at the same rate. Here we argue that a greater emphasis on falsification – the direct testing of strong hypotheses – would lead to faster progress by allowing well-specified hypotheses to be eliminated. We describe an example from neuroscience where there has been little work to directly test two prominent but incompatible hypotheses related to traumatic brain injury. Based on this example, we discuss how building strong hypotheses and then setting out to falsify them can bring greater precision to the clinical neurosciences, and argue that this approach could be beneficial to all areas of science.

The Effects of Optogenetic Activation of Astrocytes on Spike-and-Wave Discharges in Genetic Absence Epileptic Rats

Background: Absence seizures (petit mal seizures) are characterized by a brief loss of consciousness without loss of postural tone. The disease is diagnosed by an electroencephalogram (EEG) showing spike–wave discharges (SWD) caused by hypersynchronous thalamocortical (TC) oscillations. There has been an explosion of research highlighting the role of astrocytes in supporting and modulating neuronal activity. Despite established in vitro evidence, astrocytes’ influence on the TC network remains to be elucidated in vivo in the absence epilepsy (AE).

Purpose: In this study, we investigated the role of astrocytes in the generation and modulation of SWDs. We hypothesize that disturbances in astrocytes’ function may affect the pathomechanism of AE.

Methods: To direct the expression of channelrhodopsin-2 (ChR2) rAAV8-GFAP-ChR2(H134R)-EYFP or to control the effect of surgical intervention, AAV-CaMKIIa-EYFP was injected into the ventrobasal nucleus (VB) of the thalamus of 18 animals. After four weeks following the injection, rats were stimulated using blue light (~473 nm) and, simultaneously, the electrophysiological activity of the frontal cortical neurons was recorded for three consecutive days. The animals were then perfused, and the brain tissue was analyzed by confocal microscopy.

Results: A significant increase in the duration of SWD without affecting the number of SWD in genetic absence epileptic rats from Strasbourg (GAERS) compared to control injections was observed. The duration of the SWD was increased from 12.50 ± 4.41 s to 17.44 ± 6.07 following optogenetic stimulation in GAERS. The excitation of the astrocytes in Wistar Albino Glaxo Rijswijk (WAG-Rij) did not change the duration of SWD; however, stimulation resulted in a significant increase in the number of SWD from 18.52 ± 11.46 bursts/30 min to 30.17 ± 18.43 bursts/30 min. Whereas in control injection, the duration and the number of SWDs were similar at pre- and poststimulus. Both the background and poststimulus average firing rates of the SWD in WAG-Rij were significantly higher than the firing recorded in GAERS.

Conclusion: These findings suggest that VB astrocytes play a role in modulating the SWD generation in both rat models with distinct mechanisms and can present an essential target for the possible therapeutic approach for AE.

Between two stools: preclinical research, reproducibility, and statistical design of experiments

Translation of animal-based preclinical research is hampered by poor validity and reproducibility issues. Unfortunately, preclinical research has 'fallen between the stools' of competing study design traditions. Preclinical studies are often characterised by small sample sizes, large variability, and 'problem' data. Although Fisher-type designs with randomisation and blocking are appropriate and have been vigorously promoted, structured statistically-based designs are almost unknown. Traditional analysis methods are commonly misapplied, and basic terminology and principles of inference testing misinterpreted. Problems are compounded by the lack of adequate statistical training for researchers, and failure of statistical educators to account for the unique demands of preclinical research. The solution is a return to the basics: statistical education tailored to non-statistician investigators, with clear communication of statistical concepts, and curricula that address design and data issues specific to preclinical research. Statistics curricula should focus on statistics as process: data sampling and study design before analysis and inference. Properly-designed and analysed experiments are a matter of ethics as much as procedure. Shifting the focus of statistical education from rote hypothesis testing to sound methodology will reduce the numbers of animals wasted in noninformative experiments and increase overall scientific quality and value of published research.

The Prevalence of Depression and Related Factors During the COVID-19 Pandemic Among the General Population of the Jazan Region of Saudi Arabia

Background This study examines the rates of depression associated with the COVID-19 pandemic along with mitigation measures such as lockdown and quarantine in the population of the Jazan region in Saudi Arabia. The Kingdom of Saudi Arabia (KSA) began mitigation measures before the first case appeared on March 2, 2020, disrupting daily life in a culture that is centered on family life. We sought to assess the psychological impacts of the pandemic on this culturally unique region to see if it affected as many as other reported places in the world. Methods A self-reporting online questionnaire in Arabic was distributed through social media applications and a convenience sample of 942 participants ≥18 years of age living in the Jazan region was selected. The questionnaire included socio-demographics, economic status, chronic medical conditions, focus on and knowledge of COVID-19, and the patient health questionnaire-9 scale (PHQ-9) for depression metrics. The data in this study were analyzed using descriptive analysis of participant characteristics, followed by Chi-square testing to compare reported depression related to each variable. Finally, to control for confounding factors, we applied multivariate logistic regression to find an adjusted odds ratio (AOR) with a 95% CI. Results In the Jazan region, the rate of depression during the COVID-19 pandemic was nearly 26%. There are several significant determinants associated with higher rates of depression in descending order: those with chronic diseases were 160% higher than those without; those with a history of mental illness were 150% higher; participants who focused excessively on the pandemic ≥3 hours daily were 130% higher; participants who were divorced or widowed were 120% higher than singles; females were 87% higher; those under age 40 were 57% higher; students were 50% higher; those reporting low incomes were 40% higher than those with moderate incomes and 60% higher than those with high incomes. Conclusions Strategies need to be devised to protect vulnerable groups of participants from mental health effects, including depression during the COVID-19 pandemic. This will require the collaboration of various institutions, such as schools and others, to provide support for education and mental health. Future research should be aimed at determining the reasons for this higher vulnerability of some groups.

Outcome unpredictability affects outcome-specific motivation to learn

Outcome predictability effects in associative learning paradigms describe better learning about outcomes with a history of greater predictability in a similar but unrelated task compared with outcomes with a history of unpredictability. Inspired by the similarities between this phenomenon and the effect of uncontrollability in learned helplessness paradigms, here, we investigate whether learning about unpredictability decreases outcome-specific motivation to learn. We used a modified version of the allergy task, in which participants first observe the foods eaten by a fictitious patient, followed by allergic reactions that he subsequently suffers, some of which are perfectly predictable and others unpredictable. We then implemented an active learning method in a second task in which participants could only learn about either the previously predictable or unpredictable outcomes on each trial. At the beginning of each trial, participants had to decide whether they wanted to learn about one outcome category or the other. Participants at the beginning of the second task chose to learn about the previously predictable outcomes first and to learn about the previously unpredictable outcomes in later trials. This showed that unpredictability affects future motivation to learn in other circumstances. Interestingly, we did not find any sign of outcome predictability effect at the end of the second phase, suggesting that participants compensate for biased outcome sampling when making overt choices in ways that they may not when learning about both outcome categories simultaneously.

Letter processing in Russian: Does orthography matter?

Prior research has suggested that the identification and encoding of letter positions within letter strings might be influenced by orthography. Letters in transparent languages (e.g., Greek) with regular grapheme-to-phoneme correspondences are processed sequentially, whereas letters in deep languages (e.g., English) are processed in parallel. In three experiments, we used a visual search paradigm to test this hypothesis on Russian-a relatively transparent language. In Experiment 1, we measured the identification speed of Cyrillic letters at each position in the five-element real words or pronounceable pseudowords. In Experiment 2, the performance was compared to random letter strings, and in Experiment 3, to non-linguistic symbol strings. Our results reveal a search pattern similar to English, excluding strictly serial letter computation, which is inconsistent with the orthography hypothesis. Moreover, we showed that the lexical status and the nature of the string (linguistic/non-linguistic) affect response times for Russian and therefore must be accounted for in models of visual word recognition.

Permutation tests are robust and powerful at 0.5% and 5% significance levels

Recent replication crisis has led to a number of ad hoc suggestions to decrease the chance of making false positive findings. Among them, Johnson (Proceedings of the National Academy of Sciences, 110, 19313-19317, 2013) and Benjamin et al. (Nature Human Behaviour, 2, 6-10 2018) recommend using the significance level of α = 0.005 (0.5%) as opposed to the conventional 0.05 (5%) level. Even though their suggestion is easy to implement, it is unclear whether or not the commonly used statistical tests are robust and/or powerful at such a small significance level. Therefore, the main aim of our study is to investigate the robustness and power curve behaviors of independent (unpaired) two-sample tests for metric and ordinal data at nominal significance levels of α = 0.005 and α = 0.05. Through an extensive simulation study, it is found that the permutation versions of the Welch t-test and the Brunner-Munzel test are particularly robust and powerful while the commonly used two-sample tests which utilize t-distribution tend to be either liberal or conservative, and have peculiar power curve behaviors under skewed distributions with variance heterogeneity.

Effect size, sample size and power of forced swim test assays in mice: Guidelines for investigators to optimize reproducibility

A recent flood of publications has documented serious problems in scientific reproducibility, power, and reporting of biomedical articles, yet scientists persist in their usual practices. Why? We examined a popular and important preclinical assay, the Forced Swim Test (FST) in mice used to test putative antidepressants. Whether the mice were assayed in a naïve state vs. in a model of depression or stress, and whether the mice were given test agents vs. known antidepressants regarded as positive controls, the mean effect sizes seen in the experiments were indeed extremely large (1.5-2.5 in Cohen's d units); most of the experiments utilized 7-10 animals per group which did have adequate power to reliably detect effects of this magnitude. We propose that this may at least partially explain why investigators using the FST do not perceive intuitively that their experimental designs fall short-even though proper prospective design would require ~21-26 animals per group to detect, at a minimum, large effects (0.8 in Cohen's d units) when the true effect of a test agent is unknown. Our data provide explicit parameters and guidance for investigators seeking to carry out prospective power estimation for the FST. More generally, altering the real-life behavior of scientists in planning their experiments may require developing educational tools that allow them to actively visualize the inter-relationships among effect size, sample size, statistical power, and replicability in a direct and intuitive manner.

Improving drug safety predictions by reducing poor analytical practices

Predicting the safety of a drug from preclinical data is a major challenge in drug discovery, and progressing an unsafe compound into the clinic puts patients at risk and wastes resources. In drug safety pharmacology and related fields, methods and analytical decisions known to provide poor predictions are common and include creating arbitrary thresholds, binning continuous values, giving all assays equal weight, and multiple reuse of information. In addition, the metrics used to evaluate models often omit important criteria and models’ performance on new data are often not assessed rigorously. Prediction models with these problems are unlikely to perform well, and published models suffer from many of these issues. We describe these problems in detail, demonstrate their negative consequences, and propose simple solutions that are standard in other disciplines where predictive modelling is used.

Quantifying the benefits of using decision models with response time and accuracy data

Response time and accuracy are fundamental measures of behavioral science, but discerning participants' underlying abilities can be masked by speed-accuracy trade-offs (SATOs). SATOs are often inadequately addressed in experiment analyses which focus on a single variable or which involve a suboptimal analytic correction. Models of decision-making, such as the drift diffusion model (DDM), provide a principled account of the decision-making process, allowing the recovery of SATO-unconfounded decision parameters from observed behavioral variables. For plausible parameters of a typical between-groups experiment, we simulate experimental data, for both real and null group differences in participants' ability to discriminate stimuli (represented by differences in the drift rate parameter of the DDM used to generate the simulated data), for both systematic and null SATOs. We then use the DDM to fit the generated data. This allows the direct comparison of the specificity and sensitivity for testing of group differences of different measures (accuracy, reaction time, and the drift rate from the model fitting). Our purpose here is not to make a theoretical innovation in decision modeling, but to use established decision models to demonstrate and quantify the benefits of decision modeling for experimentalists. We show, in terms of reduction of required sample size, how decision modeling can allow dramatically more efficient data collection for set statistical power; we confirm and depict the non-linear speed-accuracy relation; and we show how accuracy can be a more sensitive measure than response time given decision parameters which reasonably reflect a typical experiment.

The psychology of experimental psychologists: Overcoming cognitive constraints to improve research: The 47th Sir Frederic Bartlett Lecture

Like many other areas of science, experimental psychology is affected by a "replication crisis" that is causing concern in many fields of research. Approaches to tackling this crisis include better training in statistical methods, greater transparency and openness, and changes to the incentives created by funding agencies, journals, and institutions. Here, I argue that if proposed solutions are to be effective, we also need to take into account human cognitive constraints that can distort all stages of the research process, including design and execution of experiments, analysis of data, and writing up findings for publication. I focus specifically on cognitive schemata in perception and memory, confirmation bias, systematic misunderstanding of statistics, and asymmetry in moral judgements of errors of commission and omission. Finally, I consider methods that may help mitigate the effect of cognitive constraints: better training, including use of simulations to overcome statistical misunderstanding; specific programmes directed at inoculating against cognitive biases; adoption of Registered Reports to encourage more critical reflection in planning studies; and using methods such as triangulation and "pre mortem" evaluation of study design to foster a culture of dialogue and criticism.

Testing the interhemispheric deficit theory of dyslexia using the visual half-field technique

A deficit in interhemispheric transfer has been proposed as a neuropsychological theory of dyslexia. Interactions between the hemispheres during word recognition can be studied using the visual half-field paradigm. The well-established recognition advantage for right visual field (RVF) words over left visual field (LVF) words is thought to reflect the additional processing costs associated with callosal transfer of LVF word representations to the language-specialised left hemisphere. In addition, a further gain in recognition for bilateral presentation of a word has been attributed to cooperative interactions between the hemispheres. These recognition advantages can therefore be seen as behavioural indices of the efficiency of callosal transfer. This study aimed to replicate the finding of an absence of the bilateral advantage in developmental dyslexia, previously reported by Henderson et al. In all, 47 dyslexic and 43 control adult participants were tested, and no significant difference was found in the size of the bilateral advantage between the two groups. Our data did however replicate the previous finding of an increased RVF-LVF difference in dyslexic participants caused by poorer accuracy for LVF words (i.e., a greater LVF cost). This evidence is compatible with the interhemispheric deficit theory of dyslexia, suggesting an impairment in the transfer of visual word information from the right to the left hemisphere during reading.

Improving transparency and scientific rigor in academic publishing

Progress in basic and clinical research is slowed when researchers fail to provide a complete and accurate report of how a study was designed, executed, and the results analyzed. Publishing rigorous scientific research involves a full description of the methods, materials, procedures, and outcomes. Investigators may fail to provide a complete description of how their study was designed and executed because they may not know how to accurately report the information or the mechanisms are not in place to facilitate transparent reporting. Here, we provide an overview of how authors can write manuscripts in a transparent and thorough manner. We introduce a set of reporting criteria that can be used for publishing, including recommendations on reporting the experimental design and statistical approaches. We also discuss how to accurately visualize the results and provide recommendations for peer reviewers to enhance rigor and transparency. Incorporating transparency practices into research manuscripts will significantly improve the reproducibility of the results by independent laboratories. SIGNIFICANCE: Failure to replicate research findings often arises from errors in the experimental design and statistical approaches. By providing a full account of the experimental design, procedures, and statistical approaches, researchers can address the reproducibility crisis and improve the sustainability of research outcomes. In this piece, we discuss the key issues leading to irreproducibility and provide general approaches to improving transparency and rigor in reporting, which could assist in making research more reproducible.

Improving transparency and scientific rigor in academic publishing

Progress in basic and clinical research is slowed when researchers fail to provide a complete and accurate report of how a study was designed, executed, and the results analyzed. Publishing rigorous scientific research involves a full description of the methods, materials, procedures, and outcomes. Investigators may fail to provide a complete description of how their study was designed and executed because they may not know how to accurately report the information or the mechanisms are not in place to facilitate transparent reporting. Here, we provide an overview of how authors can write manuscripts in a transparent and thorough manner. We introduce a set of reporting criteria that can be used for publishing, including recommendations on reporting the experimental design and statistical approaches. We also discuss how to accurately visualize the results and provide recommendations for peer reviewers to enhance rigor and transparency. Incorporating transparency practices into research manuscripts will significantly improve the reproducibility of the results by independent laboratories.

Improving transparency and scientific rigor in academic publishing

Progress in basic and clinical research is slowed when researchers fail to provide a complete and accurate report of how a study was designed, executed, and the results analyzed. Publishing rigorous scientific research involves a full description of the methods, materials, procedures, and outcomes. Investigators may fail to provide a complete description of how their study was designed and executed because they may not know how to accurately report the information or the mechanisms are not in place to facilitate transparent reporting. Here, we provide an overview of how authors can write manuscripts in a transparent and thorough manner. We introduce a set of reporting criteria that can be used for publishing, including recommendations on reporting the experimental design and statistical approaches. We also discuss how to accurately visualize the results and provide recommendations for peer reviewers to enhance rigor and transparency. Incorporating transparency practices into research manuscripts will significantly improve the reproducibility of the results by independent laboratories.

Training in experimental design and statistics is essential: Response to Jordan

This Formal Comment responds to Jordan et al., and stresses that if scientific findings are to be robust, training in experimental design and statistics is critical to ensure that research questions, design considerations, and analyses are aligned.