"Tabela falante" como estratégia de integração de dados em uma pesquisa de métodos mistos / "Tabla parlante" como estrategia de integración de datos en una investigación de métodos mixtos / "Talking table" as a data integration strategy in mixed methods research

RESUMO Objetivo relatar a utilização da tabela falante como estratégia de integração e análise de dados em estudo de abordagem mista. Método trata-se de um relato de utilização de uma estratégia metodológica de integração e análise dos dados em pesquisa de método misto. São apresentados dados de um estudo longitudinal analítico, que acompanhou 151 lactentes prematuros no primeiro ano de vida. O estudo abordou aspectos das condições de saúde dessa população e integrou dados quantitativos, coletados por meio de instrumento de avaliação de condições de saúde e dados qualitativos oriundos de entrevista semiestruturada. Resultados a integração dos dados em estudos mistos é uma exigência metodológica que requer dos pesquisadores a utilização de estratégias que possibilitem e facilitem esse processo analítico. A tabela falante, por meio da integração visual dos dados quantitativos expressos em tabelas e suas convergências e divergências analíticas com os enunciados qualitativos, favorece a leitura e interpretação integrada. Conclusão e implicações para a prática considera-se a tabela falante uma ferramenta analítica de integração de dados quantitativos e qualitativos que contribui na formulação de metainferências em pesquisas com métodos mistos.

RESUMEN Objetivo relatar el uso de la mesa parlante como estrategia de análisis e integración de datos en un estudio de enfoque mixto. Método este es un informe sobre el uso de una estrategia metodológica para la integración y el análisis de datos en la investigación de método mixto. Se presentan los datos de un estudio longitudinal analítico que siguió a 151 bebés prematuros en el primer año de vida. Nuestro estudio abordó aspectos de las condiciones de salud de esta población e integró datos cuantitativos, recolectados a través de un instrumento para evaluar las condiciones de salud y datos cualitativos de una entrevista semiestructurada. Resultados la integración de datos en estudios mixtos es un requisito metodológico que obliga a los investigadores a utilizar estrategias que habiliten y faciliten este proceso analítico. La mesa parlante, a través de la integración visual de datos cuantitativos expresados en tablas y sus convergencias y divergencias analíticas con enunciados cualitativos, favorece la lectura e interpretación integradas. Conclusión e implicaciones para la práctica: la mesa de diálogo es considerada como una herramienta analítica para la integración de datos cuantitativos y cualitativos que contribuyen a la formulación de meta-inferencias en investigaciones con métodos mixtos.

ABSTRACT Objective to report the use of a talking table as a data analysis and integration strategy in a mixed approach study. Method this is a report on the use of a methodological strategy for data integration and analysis in mixed methods research. Data from an analytical longitudinal study that followed 151 preterm infants in the first year of life are presented. The study addressed aspects of the health conditions of this population and integrated quantitative data, collected through an instrument to assess health conditions and qualitative data from a semi-structured interview. Results data integration in mixed studies is a methodological requirement that requires researchers to use strategies that enable and facilitate this analytical process. A talking table, through the visual integration of quantitative data expressed in tables and their analytical convergences and divergences with qualitative statements, favors integrated reading and interpretation. Conclusion and implications for practice: a talking table is considered an analytical tool for quantitative and qualitative data integration, which contribute to developing meta-inferences in mixed methods research.

Procedures for Comparison of Two Means in Independent Groups with R

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A simple method for unsupervised anomaly detection: An application to Web time series data.

We propose a simple anomaly detection method that is applicable to unlabeled time series data and is sufficiently tractable, even for non-technical entities, by using the density ratio estimation based on the state space model. Our detection rule is based on the ratio of log-likelihoods estimated by the dynamic linear model, i.e. the ratio of log-likelihood in our model to that in an over-dispersed model that we will call the NULL model. Using the Yahoo S5 data set and the Numenta Anomaly Benchmark data set, publicly available and commonly used benchmark data sets, we find that our method achieves better or comparable performance compared to the existing methods. The result implies that it is essential in time series anomaly detection to incorporate the specific information on time series data into the model. In addition, we apply the proposed method to unlabeled Web time series data, specifically, daily page view and average session duration data on an electronic commerce site that deals in insurance goods to show the applicability of our method to unlabeled real-world data. We find that the increase in page view caused by e-mail newsletter deliveries is less likely to contribute to completing an insurance contract. The result also suggests the importance of the simultaneous monitoring of more than one time series.

Quantile estimation of semiparametric model with time-varying coefficients for panel count data.

Panel count data frequently occurs in follow-up studies, such as medical research, social sciences, reliability studies, and tumorigenicity experiences. This type data has been extensively studied by various statistical models with time-invariant regression coefficients. However, the assumption of invariant coefficients may be violated in some reality, and the temporal covariate effects would be of great interest in research studies. This motivates us to consider a more flexible time-varying coefficient model. For statistical inference of the unknown functions, the quantile regression approach based on the B-spline approximation is developed. Asymptotic results on the convergence of the estimators are provided. Some simulation studies are presented to assess the finite-sample performance of the estimators. Finally, two applications of bladder cancer data and US flight delay data are analyzed by the proposed method.

Seven steps toward more transparency in statistical practice.

We argue that statistical practice in the social and behavioural sciences benefits from transparency, a fair acknowledgement of uncertainty and openness to alternative interpretations. Here, to promote such a practice, we recommend seven concrete statistical procedures: (1) visualizing data; (2) quantifying inferential uncertainty; (3) assessing data preprocessing choices; (4) reporting multiple models; (5) involving multiple analysts; (6) interpreting results modestly; and (7) sharing data and code. We discuss their benefits and limitations, and provide guidelines for adoption. Each of the seven procedures finds inspiration in Merton's ethos of science as reflected in the norms of communalism, universalism, disinterestedness and organized scepticism. We believe that these ethical considerations-as well as their statistical consequences-establish common ground among data analysts, despite continuing disagreements about the foundations of statistical inference.

Study the Effect of the Risk Factors in the Estimation of the Breast Cancer Risk Score Using Machine Learning.

OBJECTIVE: Early prediction of breast cancer is one of the most essential fields of medicine. Many studies have introduced prediction approaches to facilitate the early prediction and estimate the future occurrence based on mammography periodic tests. In the current research, we introduce a novel machine learning tool for the early prediction of breast cancer. METHODS: Three basic resources are used to identify the most essential risk factors; including the BCSC (Breast Cancer Surveillance Consortium) dataset, a medical questionnaire, and multiple international breast cancer reports. The BCSC dataset has been normalized and balanced; consequently, the questionnaire and the medical reports are analyzed in order to define the degree of importance and a potential weight factor of each risk factor. These weights are used to scale risk factors and then the optimizable tree-based ML model is trained using the balanced weighted risk factors datasets. RESULTS: Three balanced versions of the BCSC dataset are used; oversampled, down-sampled and mixed datasets. Each risk factor has a weight (1, 2 or 4) assigned based on a mathematical modelling of the questionnaire and the international breast cancer reports. The experiments are applied on the weighted and non-weighted versions of the database, and they indicate that the performance increases significantly by using the weighted version of the risk factors. The tests prove that the down-weighting of the non-essential risk factor increases the accuracy and reduces errors. The overall accuracy of the weighted balanced datasets reaches 100%, 95.8% and 95.9% for down-sampled, oversampled and mixed datasets respectively. CONCLUSION: Weighting the risk factors of the BCSC dataset improves the performance by increasing the accuracy and reducing the false rejection and false discovery rates for all versions of balanced datasets. The weighting approach can also be used to improve the estimation score of breast cancer by scaling the individual scores of risk factors.

A New Clinical Model to Estimate the Pre-Test Probability of Cushing's Syndrome: The Cushing Score.

Background: Hypercortisolism accounts for relevant morbidity and mortality and is often a diagnostic challenge for clinicians. A prompt diagnosis is necessary to treat Cushing's syndrome as early as possible. Objective: The aim of this study was to develop and validate a clinical model for the estimation of pre-test probability of hypercortisolism in an at-risk population. Design: We conducted a retrospective multicenter case-control study, involving five Italian referral centers for Endocrinology (Turin, Messina, Naples, Padua and Rome). One hundred and fifty patients affected by Cushing's syndrome and 300 patients in which hypercortisolism was excluded were enrolled. All patients were evaluated, according to current guidelines, for the suspicion of hypercortisolism. Results: The Cushing score was built by multivariable logistic regression, considering all main features associated with a clinical suspicion of hypercortisolism as possible predictors. A stepwise backward selection algorithm was used (final model AUC=0.873), then an internal validation was performed through ten-fold cross-validation. Final estimation of the model performance showed an average AUC=0.841, thus reassuring about a small overfitting effect. The retrieved score was structured on a 17.5-point scale: low-risk class (score value: ≤5.5, probability of disease=0.8%); intermediate-low-risk class (score value: 6-8.5, probability of disease=2.7%); intermediate-high-risk class (score value: 9-11.5, probability of disease=18.5%) and finally, high-risk class (score value: ≥12, probability of disease=72.5%). Conclusions: We developed and internally validated a simple tool to determine pre-test probability of hypercortisolism, the Cushing score, that showed a remarkable predictive power for the discrimination between subjects with and without a final diagnosis of Cushing's syndrome.

Comparison of Methods to Estimate Low-Density Lipoprotein Cholesterol in Patients With High Triglyceride Levels.

Importance: Low-density lipoprotein cholesterol (LDL-C) is typically estimated with the Friedewald or Martin/Hopkins equation; however, if triglyceride levels are 400 mg/dL or greater, laboratories reflexively perform direct LDL-C (dLDL-C) measurement. The use of direct chemical LDL-C assays and estimation of LDL-C via the National Institutes of Health Sampson equation are not well validated, and data on the accuracy of LDL-C estimation at higher triglyceride levels are limited. Objective: To compare an extended Martin/Hopkins equation for triglyceride values of 400 to 799 mg/dL with the Friedewald and Sampson equations. Design, Setting, and Participants: This cross-sectional study evaluated consecutive patients at clinical sites across the US with patient lipid distributions representative of the US population in the Very Large Database of Lipids from January 1, 2006, to December 31, 2015, with triglyceride levels of 400 to 799 mg/dL. Data analysis was performed from November 9, 2020, to March 23, 2021. Main Outcomes and Measures: Accuracy in LDL-C classification according to guideline-based categories and absolute errors between estimated LDL-C and dLDL-C levels. Patients were randomly assigned 2:1 to derivation and validation data sets. Levels of dLDL-C were measured by vertical spin-density gradient ultracentrifugation. The LDL-C levels were estimated using the Friedewald method, with a fixed ratio of triglycerides to very low-density lipoprotein cholesterol (VLDL-C ratio of 5:1), extended Martin/Hopkins equation with a flexible ratio, and Sampson equation with VLDL-C estimation by multiple least-squares regression. Results: A total of 111 939 patients (mean [SD] age, 52 [13] years; 65.0% male) with triglyceride levels of 400 to 799 mg/dL were included, representing 2.2% of 5 081 680 patients in the database. Across all individual guideline LDL-C classes (<40, 40-69, 70-99, 100-129, 130-159, 160-189, and ≥190), estimation of LDL-C by the extended Martin/Hopkins equation was most accurate (62.1%) compared with the Friedewald (19.3%) and Sampson (40.4%) equations. In classifying LDL-C levels less than 70 mg/dL across all triglyceride strata, the extended Martin/Hopkins equation was most accurate (67.3%) compared with Friedewald (5.1%) and Sampson (26.4%) equations. In addition, for classifying LDL-C levels less than 40 mg/dL across all triglyceride strata, the extended Martin/Hopkins equation was most accurate (57.2%) compared with the Friedewald (4.3%) and Sampson (14.4%) equations. However, considerable underclassification of LDL-C occurred. The magnitude of error between the Martin/Hopkins equation estimation and dLDL-C was also smaller: at LDL-C levels less than 40 mg/dL, 2.7% of patients had 30 mg/dL or greater differences between dLDL-C and estimated LDL-C using the Martin/Hopkins equation compared with the Friedewald (92.5%) and Sampson (38.7%) equations. Conclusions and Relevance: In this cross-sectional study, the extended Martin/Hopkins equation offered greater LDL-C accuracy compared with the Friedewald and Sampson equations in patients with triglyceride levels of 400 to 799 mg/dL. However, regardless of method used, caution is advised with LDL-C estimation in this triglyceride range.

Bedside estimates of dead space using end-tidal CO2 are independently associated with mortality in ARDS.

PURPOSE: In acute respiratory distress syndrome (ARDS), dead space fraction has been independently associated with mortality. We hypothesized that early measurement of the difference between arterial and end-tidal CO2 (arterial-ET difference), a surrogate for dead space fraction, would predict mortality in mechanically ventilated patients with ARDS. METHODS: We performed two separate exploratory analyses. We first used publicly available databases from the ALTA, EDEN, and OMEGA ARDS Network trials (N = 124) as a derivation cohort to test our hypothesis. We then performed a separate retrospective analysis of patients with ARDS using University of Chicago patients (N = 302) as a validation cohort. RESULTS: The ARDS Network derivation cohort demonstrated arterial-ET difference, vasopressor requirement, age, and APACHE III to be associated with mortality by univariable analysis. By multivariable analysis, only the arterial-ET difference remained significant (P = 0.047). In a separate analysis, the modified Enghoff equation ((PaCO2-PETCO2)/PaCO2) was used in place of the arterial-ET difference and did not alter the results. The University of Chicago cohort found arterial-ET difference, age, ventilator mode, vasopressor requirement, and APACHE II to be associated with mortality in a univariate analysis. By multivariable analysis, the arterial-ET difference continued to be predictive of mortality (P = 0.031). In the validation cohort, substitution of the arterial-ET difference for the modified Enghoff equation showed similar results. CONCLUSION: Arterial to end-tidal CO2 (ETCO2) difference is an independent predictor of mortality in patients with ARDS.

Testing Internal Quality Control of Clinical Laboratory Data Using Paired t-Test under Uncertainty.

The existing paired t-test under classical statistics cannot be applied when the data is obtained from the complex process, having interval, uncertainty, indeterminacy, and incompleteness. In this paper, the modification of the paired t-test under neutrosophic statistics is proposed. The testing criterion of the proposed paired t-test is given. The application of the proposed paired t-test is given using the interval quality control of clinical laboratory data. From the analysis, it can be seen than the proposed test is quite effective and informative to apply for testing the measurement tools in the clinical laboratory.

Sensitive proportion in ranked set sampling.

This paper considers the concomitant-based rank set sampling (CRSS) for estimation of the sensitive proportion. It is shown that CRSS procedure provides an unbiased estimator of the population sensitive proportion, and it is always more precise than corresponding sample sensitive proportion (Warner SL (1965)) that based on simple random sampling (SRS) without increasing sampling cost. Additionally, a new estimator based on ratio method is introduced using CRSS protocol, preserving the respondent's confidentiality through a randomizing device. The numerical results of these estimators are obtained by using numerical integration technique. An application to real data is also given to support the methods.

Marking fin spine of juvenile sturgeon (Acipenseriformes: Acipenseridae) using oxytetracycline and the comparing of growth performance / [Marcação da espinha da nadadeira de esturjão juvenil (Acipenseriformes: Acipenseridae) usando-se oxitetraciclina e comparação do desempenho de crescimento]

This study aimed to describe and validate the formation of the rings in the spine of the pectoral fin and to determine the coherence of the OTC mark with the rings of three species of Caspian Sea sturgeon, the Persian sturgeon (Acipenser persicus), the Starry sturgeon (Acipenser stellatus) and Ship sturgeon (Acipenser nudiventris). Validation was achieved by comparing the total radius of the fin spine of fish of known age after one and two years of growth with the measured radius of the first and second rings in the zone. There was no overlap between the measured radius for the first year and the increase for the second. The Ship sturgeon showed the largest width of the second ring followed by the Persian sturgeon and Stellate sturgeon. The results indicate that the highest growth parameter belongs to the juvenile Ship sturgeon. This research showed that chemically marking the fin spines of juvenile Acipenseridae leads to unbiased estimates and contributes to the knowledge of the population dynamics of these species. The study found that the combination of the dial ring of the pectoral fin spine with growth validated the age estimation in juvenile sturgeon Ship, Persian, and Starry sturgeon.(AU)

O objetivo deste estudo foi descrever e validar a formação dos anéis na espinha da nadadeira peitoral de três espécies de esturjão do mar Cáspio: o esturjão-persa (Acipenser persicus), o esturjão-estrelado (Acipenser stellatus) e o esturjão-de-navio (Acipenser nudiventris), bem como determinar a coerência da marca OTC com os anéis dessas três espécies. A validação foi alcançada comparando-se o raio total da espinha da nadadeira de peixes de idade conhecida, após um e dois anos de crescimento, com o raio medido do primeiro e segundo anéis na zona. Não houve sobreposição entre o raio medido no primeiro ano e o aumento no segundo. O esturjão-de-navio mostrou a maior largura do segundo anel, seguido pelo esturjão-persa e pelo esturjão-estrelado. Os resultados indicam que o maior parâmetro de crescimento pertence ao esturjão-de-navio juvenil. Esta pesquisa mostrou que a marcação química dos espinhos das nadadeiras de juvenis de Acipenseridae leva a estimativas imparciais e contribui para o conhecimento da dinâmica populacional dessas espécies. O estudo descobriu que a combinação do anel do mostrador da barbatana peitoral espinhal com o crescimento validou a estimativa de idade em esturjão-de-navio juvenil, esturjão-persa e esturjão-estrelado.(AU)

Reliability of last menstrual period recall, an early ultrasound and a Smartphone App in predicting date of delivery and classification of preterm and post-term births.

BACKGROUND: A reliable expected date of delivery (EDD) is important for pregnant women in planning for a safe delivery and critical for management of obstetric emergencies. We compared the accuracy of LMP recall, an early ultrasound (EUS) and a Smartphone App in predicting the EDD in South African pregnant women. We further evaluated the rates of preterm and post-term births based on using the different measures. METHODS: This is a retrospective sub-study of pregnant women enrolled in a randomized controlled trial between October 2017-December 2019. EDD and gestational age (GA) at delivery were calculated from EUS, LMP and Smartphone App. Data were analysed using SPSS version 25. A Bland-Altman plot was constructed to determine the limits of agreement between LMP and EUS. RESULTS: Three hundred twenty-five pregnant women who delivered at term (≥ 37 weeks by EUS) and without pregnancy complications were included in this analysis. Women had an EUS at a mean GA of 16 weeks and 3 days). The mean difference between LMP dating and EUS is 0.8 days with the limits of agreement 31.4-30.3 days (Concordance Correlation Co-efficient 0.835; 95%CI 0.802, 0.867). The mean(SD) of the marginal time distribution of the two methods differ significantly (p = 0.00187). EDDs were < 14 days of the actual date of delivery (ADD) for 287 (88.3%;95%CI 84.4-91.4), 279 (85.9%;95%CI 81.6-89.2) and 215 (66.2%;95%CI 60.9-71.1) women for EUS, Smartphone App and LMP respectively but overall agreement between EUS and LMP was only 46.5% using a five category scale for EDD-ADD with a kappa of .22. EUS 14-24 weeks and EUS < 14 weeks predicted EDDs < 14 days of ADD in 88.1% and 79.3% of women respectively. The proportion of births classified as preterm (< 37 weeks) was 9.9% (95%CI 7.1-13.6) by LMP and 0.3% (95%CI 0.1-1.7) by Smartphone App. The proportion of post-term (> 42 weeks gestation) births was 11.4% (95%CI 8.4-15.3), 1.9% (95%CI 0.9-3.9) and 3.4% (95%CI 1.9-5.9) by LMP, EUS and Smartphone respectively. CONCLUSIONS: EUS and Smartphone App were the most accurate to estimate the EDD in pregnant women. LMP-based dating resulted in misclassification of a significantly greater number of preterm and post-term deliveries compared to EUS and the Smartphone App.

Improved individual and population-level HbA1c estimation using CGM data and patient characteristics.

Machine learning and linear regression models using CGM and participant data reduced HbA1c estimation error by up to 26% compared to the GMI formula, and exhibit superior performance in estimating the median of HbA1c at the cohort level, potentially of value for remote clinical trials interrupted by COVID-19.

Are adults just big kids? Can the newer paediatric weight estimation systems be used in adults?

BACKGROUND: The weight of a patient is an important variable that impacts on their medical care. Although some drugs are prescribed on a so-called 'adult dose' basis, we know that adults come in all shapes and sizes - a 'one-dose-fits-all' approach is not necessarily appropriate. As a measured weight may not always be available, an alternative method of accurately estimating weight is required. OBJECTIVES: To assess and compare the accuracy of weight estimations in adults by patient self-estimation, the Mercy method, Buckley method, Broca index and PAWPER XL-MAC (paediatric advanced weight prediction in the emergency room eXtra length/eXtra large mid-arm circumference) method. METHODS: This was a prospective, cross-sectional study conducted at a tertiary academic hospital in a metropolitan area of Johannesburg, South Africa. Anthropometric variables of height, abdominal circumference, thigh circumference, mid-arm circumference and humeral length were measured. These variables were then applied to the various weight estimation methods and compared with the patient's actual weight. RESULTS: There were 188 adult patients included in the study. None of the methodologies evaluated in this study achieved the recommended >70% of weight estimations within 10% of the patient's actual weight (PW10). The Mercy method was the closest to achieving greater than the recommended 95% for weight estimation falling within 20% of the patient's actual weight (PW20). The PW20 for the Mercy method was 91.5%. The PAWPER XL-MAC and patient self-estimate methods achieved a PW20 of 85.1% and 86.1%, respectively. The Broca and Buckley methods performed poorly overall. CONCLUSIONS: None of the evaluated weight estimation methodologies was accurate enough for use in adult weight estimation. The Mercy and PAWPER XL-MAC methodologies both showed significant promise for use in adult weight estimation, but need further refinement. Although patient self-estimates were similarly accurate to those found in previous studies, they were not an accurate option; self-estimations would remain the first choice if the patient was able to provide such an estimation. The Broca index and Buckley method cannot be recommended owing to their poor performance.

Using Genetic Marginal Effects to Study Gene-Environment Interactions with GWAS Data.

Gene-environment interactions (GxE) play a central role in the theoretical relationship between genetic factors and complex traits. While genome wide GxE studies of human behaviors remain underutilized, in part due to methodological limitations, existing GxE research in model organisms emphasizes the importance of interpreting genetic associations within environmental contexts. In this paper, we present a framework for conducting an analysis of GxE using raw data from genome wide association studies (GWAS) and applying the techniques to analyze gene-by-age interactions for alcohol use frequency. To illustrate the effectiveness of this procedure, we calculate genetic marginal effects from a GxE GWAS analysis for an ordinal measure of alcohol use frequency from the UK Biobank dataset, treating the respondent's age as the continuous moderating environment. The genetic marginal effects clarify the interpretation of the GxE associations and provide a direct and clear understanding of how the genetic associations vary across age (the environment). To highlight the advantages of our proposed methods for presenting GxE GWAS results, we compare the interpretation of marginal genetic effects with an interpretation that focuses narrowly on the significance of the interaction coefficients. The results imply that the genetic associations with alcohol use frequency vary considerably across ages, a conclusion that may not be obvious from the raw regression or interaction coefficients. GxE GWAS is less powerful than the standard "main effect" GWAS approach, and therefore require larger samples to detect significant moderated associations. Fortunately, the necessary sample sizes for a successful application of GxE GWAS can rely on the existing and on-going development of consortia and large-scale population-based studies.

Shifting the focus away from binary thinking of statistical significance and towards education for key stakeholders: revisiting the debate on whether it's time to de-emphasize or get rid of statistical significance.

There has been a long-standing controversy among scientists regarding the appropriate use of P-values and statistical significance in clinical research. This debate has resurfaced through recent calls to modify the threshold of P-value required to declare significance, or to retire statistical significance entirely. In this article, we revisit the issue by discussing: i) the connection between statistical thinking and evidence-based practice; ii) some history of statistical significance and P-values; iii) some practical challenges with statistical significance or P-value thresholds in clinical research; iv) the on-going debate on what to do with statistical significance; v) suggestions to shift the focus away from binary thinking of statistical significance and towards education for key stakeholders on research essentials including statistical thinking, critical thinking, good reporting, basic clinical research concepts and methods, and more. We then conclude with remarks and illustrations of the potential deleterious public health consequences of poor methods including selective choice of analysis approach and misguided reliance on binary use of P-values to report and interpret scientific findings.