Tutorial on Biostatistics: Sample Size and Power Calculation for Ophthalmic Studies With Correlated Binary Eye Outcomes.

Purpose: To describe and demonstrate sample size and power calculation for ophthalmic studies with a binary outcome from one or both eyes. Methods: We describe sample size and power calculation for four commonly used eye designs: (1) one-eye design or person-design: one eye per subject or outcome is at person-level; (2) paired design: two eyes per subject and two eyes are in different treatment groups; (3) two-eye design: two eyes per subject and both eyes are in the same treatment group; and (4) mixture design: mixture of one eye and two eyes per subject. For each design, we demonstrate sample size and power calculations in real ophthalmic studies. Results: Using formulas and commercial or free statistical packages including SAS, STATA, R, and PS, we calculated sample size and power. We demonstrated that different statistical packages require different parameters and provide similar, yet not identical, results. We emphasize that studies using data from two eyes of a subject need to account for the intereye correlation for appropriate sample size and power calculations. We demonstrate the gain in efficiency in designs that include two eyes of a subject compared to one-eye designs. Conclusions: Ophthalmic studies use different eye designs that include one or both eyes in the same or different treatment groups. Appropriate sample size and power calculations depend on the eye design and should account for intereye correlation when two eyes from some or all subjects are included in a study. Calculations can be executed using formulas and commercial or free statistical packages.

Biostatistical Aspects of Whole Genome Sequencing Studies: Preprocessing and Quality Control.

Rapid advances in high-throughput DNA sequencing technologies have enabled large-scale whole genome sequencing (WGS) studies. Before performing association analysis between phenotypes and genotypes, preprocessing and quality control (QC) of the raw sequence data need to be performed. Because many biostatisticians have not been working with WGS data so far, we first sketch Illumina's short-read sequencing technology. Second, we explain the general preprocessing pipeline for WGS studies. Third, we provide an overview of important QC metrics, which are applied to WGS data: on the raw data, after mapping and alignment, after variant calling, and after multisample variant calling. Fourth, we illustrate the QC with the data from the GENEtic SequencIng Study Hamburg-Davos (GENESIS-HD), a study involving more than 9000 human whole genomes. All samples were sequenced on an Illumina NovaSeq 6000 with an average coverage of 35× using a PCR-free protocol. For QC, one genome in a bottle (GIAB) trio was sequenced in four replicates, and one GIAB sample was successfully sequenced 70 times in different runs. Fifth, we provide empirical data on the compression of raw data using the DRAGEN original read archive (ORA). The most important quality metrics in the application were genetic similarity, sample cross-contamination, deviations from the expected Het/Hom ratio, relatedness, and coverage. The compression ratio of the raw files using DRAGEN ORA was 5.6:1, and compression time was linear by genome coverage. In summary, the preprocessing, joint calling, and QC of large WGS studies are feasible within a reasonable time, and efficient QC procedures are readily available.

Predicting subgroup treatment effects for a new study: Motivations, results and learnings from running a data challenge in a pharmaceutical corporation.

We present the motivation, experience, and learnings from a data challenge conducted at a large pharmaceutical corporation on the topic of subgroup identification. The data challenge aimed at exploring approaches to subgroup identification for future clinical trials. To mimic a realistic setting, participants had access to 4 Phase III clinical trials to derive a subgroup and predict its treatment effect on a future study not accessible to challenge participants. A total of 30 teams registered for the challenge with around 100 participants, primarily from Biostatistics organization. We outline the motivation for running the challenge, the challenge rules, and logistics. Finally, we present the results of the challenge, the participant feedback as well as the learnings. We also present our view on the implications of the results on exploratory analyses related to treatment effect heterogeneity.

Poor statistical reporting: do we have a reason for concern? A narrative review and recommendations.

PURPOSE OF REVIEW: The aim of the review conducted was to present recent articles indicating the need to implement statistical recommendations in the daily work of biomedical journals. RECENT FINDINGS: The most recent literature shows an unchanged percentage of journals using specialized statistical review over 20 years. The problems of finding statistical reviewers, the impractical way in which biostatistics is taught and the nonimplementation of published statistical recommendations contribute to the fact that a small percentage of accepted manuscripts contain correctly performed analysis. The statistical recommendations published for authors and editorial board members in recent years contain important advice, but more emphasis should be placed on their practical and rigorous implementation. If this is not the case, we will additionally continue to experience low reproducibility of the research. SUMMARY: There is a low level of statistical reporting these days. Recommendations related to the statistical review of submitted manuscripts should be followed more rigorously.

Covariate-guided Bayesian mixture of spline experts for the analysis of multivariate high-density longitudinal data.

With rapid development of techniques to measure brain activity and structure, statistical methods for analyzing modern brain-imaging data play an important role in the advancement of science. Imaging data that measure brain function are usually multivariate high-density longitudinal data and are heterogeneous across both imaging sources and subjects, which lead to various statistical and computational challenges. In this article, we propose a group-based method to cluster a collection of multivariate high-density longitudinal data via a Bayesian mixture of smoothing splines. Our method assumes each multivariate high-density longitudinal trajectory is a mixture of multiple components with different mixing weights. Time-independent covariates are assumed to be associated with the mixture components and are incorporated via logistic weights of a mixture-of-experts model. We formulate this approach under a fully Bayesian framework using Gibbs sampling where the number of components is selected based on a deviance information criterion. The proposed method is compared to existing methods via simulation studies and is applied to a study on functional near-infrared spectroscopy, which aims to understand infant emotional reactivity and recovery from stress. The results reveal distinct patterns of brain activity, as well as associations between these patterns and selected covariates.

Aplicación móvil para el análisis estadístico en Android / Mobile application for statistics analysis on Android

El uso de dispositivos móviles en la vida moderna es imprescindible debido a las ventajas que brindan al ofrecer nuevas posibilidades e implementar de manera virtual servicios ya establecidos. La mayor existencia de móviles que computadoras en los estudiantes de Cuba nos motivó a la realización de esta aplicación. El objetivo de este artículo es describir la aplicación nombrada Cálculos estadísticos y tasas en salud (Calc. Tasas versión 1.7) construida para realizar cálculos en un curso de Bioestadística, cubriendo gran parte del contenido de esta asignatura en la enseñanza de pregrado de las universidades médicas, así como otros contenidos de interés en esta materia. También incorpora una base de datos con información demográfica y sanitaria de Cuba y sus provincias en el período 2013-2020. Como resultado se logró independencia tecnológica al dejar de usar programas foráneos y se logró una mayor portabilidad pues funciona tanto en móviles como en computadoras utilizando un emulador de Android(AU)

The use of mobile devices in modern life is essential due to the advantages they provide, offering new possibilities and implementing virtual services. The existence of greater number of mobiles phones than computers in Cuban students motivated the realization of this application. The objective of the article is to describe the application Statistical calculations and rates in health (Calc. Rates version 1.7) built to perform calculations in a Biostatistics course, covering a large part of the content of this subject in the undergraduate teaching of medical universities, as well as other content related with this topic. It also incorporates a database with demographic and health information on Cuba and its provinces in the period 2013-2020. As a result, technological independence was achieved by stopping using foreign programs and a greater portability, since it works on both mobile phones and computers through an Android emulator(AU)

Propuesta metodológica para la validación de bases de datos aplicada a las ciencias de la salud / Methodological proposal for validation of databases applied to health sciences

La estadística es uno de los pilares de la ciencia, especialmente para describir y analizar los datos, la que ha progresado exponencialmente en los últimos años. Se le debe entender como un apoyo fundamental para la toma de decisiones en las distintas disciplinas. Los análisis exploratorios son descritos como el primer paso en la estadística, buscando organizar, representar y describir los datos, pero muchas veces este proceso se vuelve complejo, siendo importante realizar una revisión exhaustiva de la matriz de datos. Es objetivo de este manuscrito describir una propuesta metodológica para la validación de bases de datos aplicada a las ciencias de la salud. Esta metodología consta de seis etapas: cuatro de ellas obligatorias y sucesivas, y las otras dos opcionales. En la literatura médica, estos procedimientos general-mente son pasados por alto; buscamos, en consecuencia, recalcar la importancia de este proceso como previo a los análisis exploratorios.

Statistics is one of the pillars of science, especially to describe and analyze data, it has progressed exponentially in recent years. Being the fundamental support for decision-making in different disciplines. Exploratory analyzes are described as the first step in statistics, seeking to organize, represent and describe the data, but many times this process becomes complex, and it is important to carry out an exhaustive review of the data matrix. The aim of this manuscript was to describe a methodological proposal for databases validation applied to health sciences. This methodology consists of 6 stages, 4 of them compulsory and successive, and the other two, optional. In the literature these procedures are generally overlooked, our purpose is thus to emphasize the importance of this process prior to exploratory analyzes.

Análise de redes: uma abordagem de estatística multivariada para pesquisas em ciências da saúde / Network analysis: a multivariate statistical approach for health science research

A análise de redes é uma técnica estatística gráfica que permite a rápida visualização e interpretação de associações entre múltiplas variáveis. Ainda existem poucos estudos com conteúdo teórico sobre esse método, especialmente nas áreas de pesquisa da geriatria e gerontologia, as quais abrangem o estudo de diferentes variáveis sociais, clínicas ou de saúde física e mental. Os objetivos deste estudo foram apresentar os principais aspectos teóricos e demonstrar a aplicabilidade da análise de rede por meio de estudos que utilizaram essa técnica, oferecendo uma linguagem acessível para todos os níveis de conhecimento em estatística. Foram demonstrados as principais características dos gráficos, conceitos teóricos básicos e artigos científicos que utilizaram redes. O presente estudo metodológico pode auxiliar o leitor na compreensão desse método analítico, ainda pouco explorado no âmbito da pesquisa nacional. Nas áreas de geriatria e gerontologia há escassez de pesquisas que abordam essa temática, entretanto o avanço tecnológico, a disponibilidade de programas estatísticos com novos recursos de análise de dados e a divulgação de informações são fatores relevantes para a expansão do conhecimento e a utilização da análise de redes.

Network analysis is a graphical statistical technique that allows rapid visualization and interpretation of associations between multiple variables. There are still few theoretical studies on this method, especially in the areas of geriatrics and gerontology research, which cover the study of different social, clinical, or physical and mental health variables. The objectives of this study were to present the main theoretical aspects of network analysis and demonstrate its applicability by analyzing studies that used this technique, offering an accessible language for all levels of knowledge in statistics. The main characteristics of the graphs, basic theoretical concepts, and scientific articles that used networks were demonstrated. This methodological study can help the reader to understand this analytical method, which is still little explored in national research. There is a scarcity of research on this subject in the areas of geriatrics and gerontology; however, technological advances, the availability of statistical programs with new data analysis resources, and the dissemination of information are relevant factors for the expansion of knowledge and the use of network analysis in this context.

Flipped learning for teaching biostatistics to peruvian dental students / Flipped learning para el aprendizaje de bioestadística en estudiantes de odontología peruanos

Objective: To evaluate the effect of the application of a flipped learning model for teaching biostatistics to dental students in a Peruvian public university. Methodology: A quasi-experimental, crossover, longitudinal and prospective design was used. A non-probability sampling technique was employed. The sample consisted of 63 students that enrolled in the Biostatistics course at the School of Dentistry at Universidad Nacional Mayor de San Marcos. Students were divided into two groups according to their designated training schedule. The contents of two units were assessed. For the first unit (descriptive statistics), the first group was taught using the flipped learning model and the second group with the master class model. For the second unit (inferential statistics), groups were crossed over. At both periods of the study, cognitive, procedural and attitudinal skills were assessed through previously validated questionnaires. Mann-Whitney U test, Cohen is d and multiple linear regression analysis were performed. Results: the mean total score for the second unit was higher (p<0.001) in the flipped learning group (32.58) compared to the master class guided training group (27.94), presenting a Cohen's d=0.97. Procedural (9.23 versus 7.80) and attitudinal (15.63 versus 12.90) skills were on average higher in the flipped learning group. Regression analysis resulted in R2=0.245, p=0.003. Conclusion: the flipped learning method achieved a higher content learning in the second unit, compared to the master class model.

Objetivo: Evaluar el efecto de la experiencia de aplicación del modelo flipped learning para el aprendizaje de bioestadística en estudiantes de odontología de una universidad pública peruana. Metodología: Se realizó un diseño cuasi experimental de secuencia cruzada, longitudinal, prospectivo. La muestra se obtuvo de manera no probabilística y estuvo conformada por 63 estudiantes que cursaron la asignatura de Bioestadística en la Facultad de Odontología de la Universidad Nacional Mayor de San Marcos. Se conformaron dos grupos de acuerdo al horario de práctica designado y se evaluaron los contenidos de dos unidades de la asignatura. En la primera unidad (estadística descriptiva) el primer grupo fue sometido al modelo flipped learning y el segundo sometido al modelo presencial clase magistral. En la segunda unidad del curso (estadística inferencial) los grupos se cruzaron. En ambos momentos se evaluaron las capacidades cognitivas, procedimentales y actitudinales a través de cuestionarios previamente validados para el estudio. Se aplicó la prueba U de Mann-Whitney, la d de Cohen y la regresión lineal múltiple. Resultados: En la segunda unidad la puntuación media total fue mayor (p<0,001) en el grupo flipped learning (32,58) en comparación al de clase magistral-práctica dirigida (27,94) con un efecto alto d Cohen= 0,97. Las capacidades procedimentales (9,23 versus7,80) y actitudinales (15,63 versus 12,90) fueron en promedios mayores en el grupo flipped learning. Al aplicarse la regresión se halló un R2= 0,245 p=0,003. Conclusión: La aplicación del modelo flipped learning logró un mayor aprendizaje en contenidos de la segunda unidad, en comparación con el modelo presencial clase magistral en los estudiantes.

Metodologia para realizar e interpretar uma revisão sistemática e metanálise individual de dados de participantes / Methodology to perform and interpret a systematic review and individual meta-analysis of participants' data

Metanálise é o método estatístico utilizado na revisão sistemática para integrar os resultados dos estudos incluídos e aumentar o poder estatístico da pesquisa primária.Estudos de metanálise, decorrentes de uma revisão sistemática, envolvem a combinação e a análise de evidências, que são utilizadas para produzir resultados baseados em conjunto de pesquisas prévias. Métodos tradicionais de metanálise sintetizam os dados agregados obtidos de publicações de estudo, como estimativa de efeito de tratamento (odds ratio, risco relativo) e sua incerteza associada (erro padrão ou intervalo de confiança). Uma abordagem alternativa é a metanálise individual de dados de participantes ou de pacientes, nos quais os dados de nível individual bruto para cada estudo são obtidos e utilizados para síntese. O objetivo deste artigo é apresentar, de forma metodológica, como realizar e interpretar uma revisão sistemática e uma metanálise individual de dados de participantes. (AU)

A meta-analysisis the statistical method used in the systematic review to integrate the result sof includeds tudies, and to increase the statistical power of primary research. Meta-analysis studies, stemming from a systematic review, involve the combination and analysis of evidence that are used to produce results based on a set of previous research. Traditional meta-analysis methods synthesize aggreg ate data obtained from study publications, such as anestimate of treatment effect (odds ratio, relative risk) and the ir associated uncertainty (standard error or confidence interval). An alternative approach isthe individual meta-analysis of participants' or patients' data, in whichgross individual-level data for eachstudy are obtained and used for synthesis. The objective of this articleis to present a method o logical way of performing and in ter preting a systematic review and individual meta-analysisof the participants' data. (AU)

Conceptos generales en bioestadística y epidemiología clínica: estudios observacionales con diseño de cohorte / General concepts in biostatistics and clinical epidemiology: observational studies with cohort design

Los estudios con diseño de cohorte evalúan la relación entre una exposición y la ocurrencia o no de un evento de interés, comenzando el análisis desde la exposición. Habiendo sido diseños muy utilizados en algunas áreas de la medicina, como la descripción de factores de riesgo cardiovascular o los efectos de la radiación ionizante en humanos, representan una herramienta con características atractivas debido a su adaptabilidad a numerosos contextos, sobre todo en el estudio de exposiciones de baja ocurrencia. Esta revisión es la cuarta entrega de una serie metodológica sobre conceptos generales en bioestadística y epidemiología clínica desarrollada por la Cátedra de Metodología de la Investigación Científica de la Escuela de Medicina de la Universidad de Valparaíso, Chile. En este artículo, se abordan conceptos teóricos generales sobre los estudios de cohorte, considerando aspectos históricos, generalidades sobre la construcción de un estudio utilizando este diseño, presentando distintas variantes y diseños derivados de interés, y potenciales sesgos a los que se puede ver enfrentado el investigador.

Cohort studies evaluate the relationship between exposure to a specific event or phenomenon and the occurrence of an associated out-come of interest (or lack thereof). This methodological design has been widely used in certain areas of medicine, such as the study of cardiovascular risk factors and the effects of ionizing radiation in humans. It is a useful study design, especially for research involving low-occurrence exposures, because it can be easily adapted to various contexts. This article, which provides an overview of observational cohort studies, is part of a methodology series on general concepts in biostatistics and clinical epidemiology developed by the Chair of Scientific Research Methodology at the University of Valparaíso's School of Medicine in Chile. It describes historical, practical, and theoretical concepts related to cohort studies; essential elements in cohort study design, and variations and derivations of it; potential types and sources of bias in these types of observational/longitudinal studies, and various methods researchers can use to address/minimize them.

Conceptos generales en bioestadística y epidemiología clínica: estudios observacionales con diseños transversal y ecológico / General concepts in biostatistics and clinical epidemiology: observational studies with cross-sectional and ecological designs

Los estudios observacionales analizan las variables de interés en la muestra o en la población, sin intervenir en ellas. Pueden ser meramente descriptivos si se focalizan en la descripción de las variables, o analíticos, en el caso de presentar grupos de comparación para establecer asociaciones mediante la inferencia estadística. Los estudios transversales y los estudios ecológicos, también llamados correlacionales, son dos diseños metodológicos observacionales. Los estudios transversales recogen los datos de la variable exposición y desenlace en un mismo momento, para describir sus características y eventualmente estudiar asociaciones. Los estudios ecológicos describen y analizan las correlaciones entre distintas variables, pero su unidad de análisis corresponde a datos agregados de múltiples individuos. En ambos casos no puede inferirse una relación causal, pero sí pueden establecerse asociaciones de gran interés para la investigación biomédica. Esta revisión es la segunda entrega de una serie metodológica sobre conceptos generales en bioestadística y epidemiología clínica desarrollada por la Cátedra de Metodología de la Investigación Científica de la Escuela de Medicina de la Universidad de Valparaíso, Chile. En este artículo se abordan conceptos teóricos generales sobre estudios transversales y estudios ecológicos, considerando sus aplicaciones, medidas de asociación, ventajas, desventajas y reporte. Finalmente, se discuten algunos conceptos de relevancia sobre diseños observacionales para los estudiantes de pre y posgrado de ciencias de la salud.

Observational studies evaluate variables of interest in a sample or a population, without intervening in them. They can be descriptive if they focus on the description of variables, or analytical when comparison between groups is made to establish associations through statistical inference. Cross-sectional studies and ecological­also called correlational­studies are two observational methodological designs. Cross-sectional studies collect the data of the exposure variable and the outcome at the same time, to describe characteristics of the sample or to study associations. Ecological studies describe and analyze correlations among different variables, and the unit of analysis is aggregated data from multiple individuals. In both types of studies, associations of interest for biomedical research can be established, but no causal relationships should be inferred. This is the second of a methodological series of articles on general concepts in biostatistics and clinical epidemiology developed by the Chair of Scientific Research Methodology at the School of Medicine, University of Valparaíso, Chile. In this review, we address general theoretical concepts about cross-sectional and ecological studies, including applications, measures of association, advantages, disadvantages, and reporting guidelines. Finally, we discuss some concepts about observational designs relevant to undergraduate and graduate students of health sciences.

Conceptos generales en bioestadística y epidemiología clínica: error aleatorio y error sistemático / General concepts in biostatistics and clinical epidemiology: random error and systematic error

La investigación biomédica, particularmente la que involucra a seres humanos, está siempre sometida a fuentes de error que deben ser reconocidas. El error sistemático o sesgo, se asocia con debilidades en el diseño metodológico o de la fase de ejecución del estudio. Éste afecta su validez y se valora cualitativamente. Por su parte, el error aleatorio se relaciona con las variaciones producidas por el azar, el cual puede expresarse cuantitativamente, pero nunca eliminarse. Esta revisión es la primera entrega de una serie metodológica sobre conceptos generales en bioestadística y epidemiología clínica desarrollada por la Cátedra de Metodología de la Investigación Científica de la Universidad de Valparaíso, Chile. En este artículo se abordan los conceptos teóricos asociados al error, su evaluación y control. Finalmente, se discuten algunas controversias actuales en cuanto a su conceptualización, de relevancia para estudiantes de pre y posgrado de ciencias de la salud.

Biomedical research, particularly when it involves human beings, is always subjected to sources of error that must be recognized. Systematic error or bias is associated with problems in the methodological design or during the execu-tion phase of a research project. It affects its validity and is qualitatively ap-praised. On the other hand, random error is related to variations due to chance. It may be quantitatively expressed, but never removed. This review is the first of a methodological series on general concepts in biostatistics and clin-ical epidemiology developed by the Chair of Scientific Research Methodology at the School of Medicine, University of Valparaíso, Chile. In this article, we address the theoretical concepts of error, its evaluation, and control. Finally, we discuss some current controversies in its conceptualization that are relevant to undergraduate and graduate students of health sciences.

Importance of using basic statistics adequately in clinical research / Importância do uso adequado da estatística básica nas pesquisas clínicas

Abstract Background and objective The inadequate use of basic statistics is the main responsible for scientific article misinterpretation. The purpose of this review article was to review some basic statistical topics to alert authors and readers about the importance of basic statistics proper reporting. Content A bibliographical and cross-sectional study was carried out, which analyzed publications in books and articles in the following databases: SciELO (Scientific Electronic Library Online) and PubMed (Available from the National Center for Biotechnology Information). Medical research is not free from the risk of false positive and false negative results due to the choice of statistical tests and presence of small sample sizes. Conclusion Understanding the correct use of basic statistics leads to fewer errors in reporting the results of studies performed and in the interpretation of their conclusions.

Resumo Justificativa e objetivo O uso inadequado da estatística básica é o maior responsável pelo erro de interpretação dos artigos científicos. O objetivo deste artigo de revisão foi rever alguns tópicos básicos de estatística para alertar autores e leitores sobre a importância do relato adequado da estatística básica. Conteúdo Foi feita pesquisa bibliográfica e transversal que analisou publicações em livros, artigos nas bases de dados SciELO (Scientific Electronic Library Online) e PubMed, do National Center for Biotechnology Information. Pesquisas na área médica não estão livres do risco de resultados falso positivos e falso negativos devido à escolha dos testes estatísticos e à presença de pequenos tamanhos de amostra. Conclusão A compreensão acerca do uso adequado da estatística básica propicia menores erros nos relatos dos resultados de estudos executados e na interpretação das suas conclusões.

Enseñanza de análisis de datos cualitativos. Residencia de Bioestadística. Escuela Nacional de Salud Pública (1993- 2017) / The teaching of qualitative data analysis. Residency in Biostatistics. National School of Public Health (1993-2017)

Introducción: los contenidos de análisis de datos cualitativos de la residencia de Bioestadística están contemplados en su plan de estudio desde 1981. Sus temas y estrategias docentes han cambiado a lo largo el tiempo. Objetivo: explicar las variaciones ocurridas en su impartición en cuanto a contenidos y estrategias docentes empleadas a partir de la experiencia de su actual profesora principal en la sede de La Habana. Métodos: se realizó análisis de los contenidos del curso en los programas la residencia de Bioestadística aprobados a partir de 1981. Se consideraron las experiencias de la autora que ha sido la profesora principal del curso por más de 20 años. Resultados: se eliminaron temas como Una Variable de Respuesta, se completó el de Regresión Logística y se introdujo el Análisis de Correspondencia, se perfeccionaron las clases teóricas y prácticas por el diseño de monografías docentes y la introducción de paquetes computacionales. Conclusiones: los contenidos han variado con la finalidad de lograr mayor comprensión de las técnicas que se imparten en la solución de problemas de investigación en correspondencia con el desarrollo de software y las posibilidades de contar con más computadoras para la docencia. Las estrategias docentes han cambiado en función de las facilidades informáticas y la utilización de monografías diseñadas para la residencia sobre el tema con el propósito de perfeccionar las habilidades de los residentes en el procesamiento de datos y en su análisis(AU)

Introduction: The contents of qualitative data analysis of the Biostatistics residency have been considered in its plan of studies since 1981. Such topics and teaching strategies have changed over time. Objective: To explain the variations that occurred in its teaching in terms of content and teaching strategies used from the experience of its current main professor at the Havana campus. Methods: The course's subjects were analyzed in the Biostatistics residency programs approved since 1981. The experiences of the author, who has been the course's main profesor for more than 20 years, were considered. Results: Topics such as A response variable were eliminated, Logistics regression was completed, and Correspondence analysis was introduced. Theoretical and practical lessons were improved by the design of teaching monographs and the introduction of computational packages. Conclusions: The contents have varied in order to gain better understanding of the techniques taught in the solution of research problems in correspondence with the development of software and the possibilities of having more computers for teaching. The teaching strategies have changed according to computer facilities and the use of monographs designed for the residency on the subject, in order to improve the residents' skills in data processing and analysis(AU)

Autoevaluación de la calidad del programa de la especialidad de bioestadística / Self-assessment of the quality program of the specialty Biostatistics

INTRODUCCIÓN: la acreditación en la enseñanza de postgrado es la expresión de la calidad a la que un proceso formativo. OBJETIVO: describir los indicadores de calidad del programa de estudios de la especialidad de Bioestadística. MÉTODOS: se realizó la autoevaluación del programa en el departamento de Bioestadística de la Escuela Nacional de Salud Pública en Mayo 2015, basado en Sistema de evaluación y acreditación de programas de especialidades de posgrado propuesto por el Ministerio de Educación Superior. RESULTADOS: se evidenció que los indicadores evaluados se aproximan a los estándares establecidos por la metodología empleada. CONCLUSIONES: el programa de estudios de la especialidad de Bioestadística posee los requerimientos de calidad necesarios para la formación de especialistas y su futura acreditación.

INTRODUCTION: The accrediting in a postgraduate education is the expression of quality in a formative process. OBJECTIVE: Describe indicators of quality of biostatistics specialty studies program. METHODS: By myself evaluation was making about biostatistics department at National Public Health School in May of 2015, based in evaluation system and accrediting of postgraduate specialties programs as a proposition of High Education Ministry. RESULTS: It was prove that the evaluating indicators are approximate to the establishing standards for used methodology. CONCLUSION: The biostatistics specialty studies program have the requirements of quality necessary for specialties formation and it future accreditation.

Statistical approaches for analyzing a continuous outcome in experimental studies / Métodos estadísticos para análizar un resultado continuo en estudios experimentales

In experimental studies the outcome variable is measured at initial time, usually called "baseline", and then in several times called "follow-up" measurement(s). The study question of interest in an experimental study is whether there is a significant difference effect between treatment and comparison group, after intervention. In addition, one wants to estimate the difference effect between groups. This paper studies some of the strategies, including a simulation process, that one can be used for analyzing data coming from an experimental study as above, and considers using or not using the baseline measurements. Three parametric and two non-parametric strategies are evaluated considering only one follow-up measurement. The baseline measurement is incorporated in context in these strategies.

En estudios experimentales, la variable resultado se mide en el momento inicial y luego en diversas ocasiones. De este modo, se habla de mediciones de "línea de base" y seguimiento respectivamente. Lo interesante de esta materia es poder determinar si una vez aplicada una intervención, existen diferencias significativas entre el grupo al que se asignó un tratamiento de prueba y el grupo de comparación. En este manuscrito se exponen algunas de las estrategias utilizadas para tal propósito; las que incluyen un proceso de simulación mediante datos obtenidos a partir de un estudio experimental. Tres estrategias paramétricas y dos no paramétricas se evalúan teniendo en cuenta sólo una medida de seguimiento. La medida de referencia se incorpora en el contexto de estas estrategias.