http://www.merlot.org:80/merlot/ A search of MERLOT materials Copyright 1997-2013 MERLOT. All rights reserved. Mon, 20 May 2013 05:04:59 PDT Mon, 20 May 2013 05:04:59 PDT http://www.merlot.org:80/merlot/images/merlot.gif http://www.merlot.org:80/merlot/ 44 34 http://www.merlot.org/merlot/viewMaterial.htm?id=327606 Introduction to Methods for Health Services Research and Evaluation provides an introduction to basic methods for undertaking research and program evaluation within health services organizations and systems. In addition to basic methods, the course also provides "the state of the art" in research and evaluation through the review of major completed studies. This course is recommended for students who will be carrying out policy research, social science research, or program impact evaluation within health delivery systems. It is also relevant to those who will apply the results of Health Services Research (HSR) done by others. OCW offers a snapshot of the educational content offered by JHSPH. OCW materials are not for credit towards any degrees or certificates offered by the Johns Hopkins Bloomberg School of Public Health. http://www.merlot.org/merlot/viewMaterial.htm?id=327206 This course covers the basics of R software and the key capabilities of the Bioconductor project (a widely used open source and open development software project for the analysis and comprehension of data arising from high-throughput experimentation in genomics and molecular biology and rooted in the open source statistical computing environment R), including importation and preprocessing of high-throughput data from microarrays and other platforms. Also introduces statistical concepts and tools necessary to interpret and critically evaluate the bioinformatics and computational biology literature. Includes an overview of of preprocessing and normalization, statistical inference, multiple comparison corrections, Bayesian Inference in the context of multiple comparisons, clustering, and classification/machine learning. http://www.merlot.org/merlot/viewMaterial.htm?id=681273 This sequence is an open course that provides an overview of the biochemical basis of cellular structure and function; the anabolic and catabolic processes involved in energy utilization; and cellular communication. The hierarchical organization of cellular components are discussed in terms of the structure and function of the four macromolecules: protein, lipid, carbohydrate, and nucleic acids. http://www.merlot.org/merlot/viewMaterial.htm?id=681274 This sequence is an open course that provides an overview of the biochemical basis of cellular structure and function; the anabolic and catabolic processes involved in energy utilization; and cellular communication. The hierarchical organization of cellular components are discussed in terms of the structure and function of the four macromolecules: protein, lipid, carbohydrate, and nucleic acids. http://www.merlot.org/merlot/viewMaterial.htm?id=681275 This sequence is an open course that provides an overview of the biochemical basis of cellular structure and function; the anabolic and catabolic processes involved in energy utilization; and cellular communication. The hierarchical organization of cellular components are discussed in terms of the structure and function of the four macromolecules: protein, lipid, carbohydrate, and nucleic acids. http://www.merlot.org/merlot/viewMaterial.htm?id=327642 Presents fundamental concepts in applied probability, exploratory data analysis, and statistical inference, focusing on probability and analysis of one and two samples. Topics include discrete and continuous probability models; expectation and variance; central limit theorem; inference, including hypothesis testing and confidence for means, proportions, and counts; maximum likelihood estimation; sample size determinations; elementary non-parametric methods; graphical displays; and data transformations. Learning Objectives The goal of this course is to equip biostatistics and quantitative scientists with core applied statistical concepts and methods:1) The course will refresh the mathematical, computational, statistical and probability background that students will need to take the course.2) The course will introduce students to the display and communication of statistical data. This will include graphical and exploratory data analysis using tools like scatterplots, boxplots and the display of multivariate data. In this objective, students will be required to write extensively.3) Students will learn the distinctions between the fundamental paradigms underlying statistical methodology.4) Students will learn the basics of maximum likelihood.5) Students will learn the basics of frequentist methods: hypothesis testing, confidence intervals.6) Students will learn basic Bayesian techniques, interpretation and prior specification.7) Students will learn the creation and interpretation of P values.8) Students will learn estimation, testing and interpretation for single group summaries such as means, medians, variances, correlations and rates.9) Students will learn estimation, testing and interpretation for two group comparisons such as odds ratios, relative risks and risk differences.10) Students will learn the basic concepts of ANOVA. http://www.merlot.org/merlot/viewMaterial.htm?id=327633 Presents an overview of major issues related to the design, function, management, regulation, and evaluation of health insurance and managed care plans. Provides a firm foundation in basic concepts pertaining to private and public sector health insurance/benefit plans, both as provided by employers and government agencies such as Medicaid and Medicare. Key topics include population care management techniques, provider payment, organizational integration, quality and accountability, cost-containment, and public policy. The course makes extensive use of outside experts Course is relevant for management- or policy-oriented students who will be working in, or interrelating with, public and private (both for-profit and not-for-profit) health insurance plans and organized delivery systems such as HMOs and hospital/physician "integrated" delivery systems. Course is also relevant to students who will be researching and analyzing these systems. Although the emphasis is placed on the US, the material is applicable to international students who are interested in financing and organization of highly developed medical care delivery systems in other nations. The site includes a syllabus, lecture material, assignments, readings, and links to other resources. http://www.merlot.org/merlot/viewMaterial.htm?id=327650 Presents fundamental concepts in applied probability, exploratory data analysis, and statistical inference, focusing on probability and analysis of one and two samples. Topics include discrete and continuous probability models; expectation and variance; central limit theorem; inference, including hypothesis testing and confidence for means, proportions, and counts; maximum likelihood estimation; sample size determinations; elementary non-parametric methods; graphical displays; and data transformations. Learning Objectives The goal of this course is to equip biostatistics and quantitative scientists with core applied statistical concepts and methods:1) The course will refresh the mathematical, computational, statistical and probability background that students will need to take the course.2) The course will introduce students to the display and communication of statistical data. This will include graphical and exploratory data analysis using tools like scatterplots, boxplots and the display of multivariate data. In this objective, students will be required to write extensively.3) Students will learn the distinctions between the fundamental paradigms underlying statistical methodology.4) Students will learn the basics of maximum likelihood.5) Students will learn the basics of frequentist methods: hypothesis testing, confidence intervals.6) Students will learn basic Bayesian techniques, interpretation and prior specification.7) Students will learn the creation and interpretation of P values.8) Students will learn estimation, testing and interpretation for single group summaries such as means, medians, variances, correlations and rates.9) Students will learn estimation, testing and interpretation for two group comparisons such as odds ratios, relative risks and risk differences.10) Students will learn the basic concepts of ANOVA. http://www.merlot.org/merlot/viewMaterial.htm?id=433657 This is a free textbook/online course designed to "provide a basic introduction to this topic and to help providers of reproductive health services incorporate a focus on sexuality into their services.״ There is a glossary of terms as well as case studies. http://www.merlot.org/merlot/viewMaterial.htm?id=433658 This is a free online textbook/course designed to "provide a basic introduction to the topic and to help providers of reproductive health services incorporate a focus on sexuality and sexually transmitted infections (STIs) into their services.״ There is also a glossary and cases included.