Hello, everyone, my name is Albert Ritzhaupt, and I'm going to be your facilitator these next five weeks. I am presently a faculty member at the University of Florida. I am looking forward to working with all of you, as we learn about the fundamentals of powered sample size analysis for longitudinal and multilevel research designs. In this short video, we are going to introduce the course and its organization for you. The course was developed in response to the National Institutes of Health Office of Behavioral and Social Sciences Research, in cooperation with a range of NIH institutes and centers that fund behavioral and social science research. The grant was awarded to faculty at the University of Florida and University of Colorado at Denver. My colleagues, Dr. Keith Muller and Deborah Glueck, served as the principal investigators. We would like to acknowledge our funders to show our appreciation for their support. Our inspiration for the design and content of this course was drawn from existing published behavioral and social science research that employ either longitudinal or multilevel research designs. All examples provided in the course instructional videos and power and sample size analysis problems are derived from existing studies. We chose this approach to make the course content more relevant to you. The course largely focuses on teaching conceptual knowledge needed to conduct power and sample size analysis for longitudinal and multilevel research designs. As such, we'll be introducing a powerful tool for conducting these analysis known as GLIMMPSE. This is a web-based and open-source environment that can be easily accessed and used to conduct power and sample size analysis for longitudinal and multilevel research design. All you need is an Internet connection and browser to access the tool. The tool includes a wizard-based interface for providing the inputs for power and sample size analysis calculations, and allows you to save your work as you go. You will not need to write complex programs or install software on your machine. You will be using the software to complete a series of exercises based on real-world research. Our goal is for you to be able to use the software independently for your own research designs. While this course does not emphasize mathematical notation or complex data analysis. We do expect you to have some basic working knowledge of descriptive and inferential statistics, the logic behind hypothesis testing, and a basic knowledge of research design. You will also need basic technology literacy to complete the course. If you do not feel prepared to complete this course, we encourage you to explore some of the basic inferential and research design courses available to you on the Coursera platform. As noted, we will not be making use of complex mathematical equations or esoteric jargon in the course. Instead, we approach the content from the conceptual perspective, covering the basic knowledge and skills you will need to conduct your own power and sample size analyses using GLIMMPSE. The course includes short instructional videos covering the topics in a logical and progressive sequence. All examples are derived from real-world behavioral and social science research studies. Terms will be carefully defined and examples provided. Each module includes a combination of both graded and ungraded activities to master the course objectives. You are strongly encouraged to complete all of the activities in the prescribed sequence. As shown in the table, this course is organized into five weeks, in which each week is essentially a module. The modules include instructional videos and both graded and ungraded assessment activities to help you master the course content. We anticipate each module taking approximately four to six hours to complete each week, so try your best to plan accordingly. Each week includes five or six instructional videos for you to actively watch. I chose not to record myself in the videos as a talking head or a talking torso. Interestingly, the research in online learning is not conclusive about their inclusion of the instructor in the instructional videos. All of the videos include a couple embedded assessment items, with feedback, to engage you with the course content. Notably, we will also include the PDF copies of the slides for you to print and actively take notes. The instructional videos are the primary source of instruction in this course. As the low-stakes activity and mechanism provide you with some feedback in addition to the embedded questions in the instructional videos, we also provide ungraded practice assessments with feedback in each module. As these are ungraded assessments, we provide you with detailed feedback and response correctness to help you reinforce what you know and help you learn the topics of what you don't. We suggest completing the ungraded practice assessments upon completion of the instructional videos in the module. Be sure to complete the ungraded assessments before moving on to the graded assessments. Although the discussions are ungraded activities, we ask you to participate in these discussions and take them seriously, as the final project in week five will use the information you've discussed with your peers. Each of the discussions build on each other to assist you in the process of outlining the research design that can be subjected to power and sample size analysis. You are encouraged to interact with your peers in these discussions and learn from each other. Comment on each other's research design and make suggestions or ask questions for clarification. Doing so will help you master the course objectives. To ensure the mastery of learning objectives, we have created a graded assessment for each module to demonstrate your learning. As these are graded assessments, you are expected to score at least an 80% on each graded assessment to provide evidence of your mastery. We'll provide you with response correctness when you submit these assessments. But since they are graded, we do not provide you the detailed feedback for each question. Again, be sure to watch the instructional videos in the module and complete the ungraded assessments prior to completing the graded assessment. As the goal of this course is to prepare you to conduct power and sample size analysis for longitudinal and multilevel designs independently, we have created a power and sample size analysis problem and quiz for each module. You will first be required to read a summarized study vignette to learn about the research design and extract the inputs for conducting the power or sample size analysis. Next, you will use the data you extract to fuel GLIMMPSE for your power and sample size analysis problem. All of the information from the study vignette should be used as inputs to GLIMMPSE to provide the power and sample size estimates. Finally, we created a short quiz to ensure you were able to run the calculations using GLIMMPSE. These are the primary assessment activities in each week, and provide you practice to apply the knowledge to real-world problem. To assist you in learning the GLIMMPSE software, the first two weeks of the course will include instructional videos to illustrate the process. After, you will be expected to use the GLIMMPSE software independently to run the models. Using the information from the previous four discussions, you will be expected to present a two-page summary of a research design that can be used for power and sample size analysis. While we'd love for you to use real numbers and parameters for this activity, it would take too long and require access to academic databases and your target population for which you would be able to generate the actual power and sample size analysis. So the next best thing is to propose a longitudinal or multilevel research design that can subsequently be used to drive sample size and power estimates after you've done enough research or run your pilot studies. Upon completion of research design document, your peers will be assigned to review your product using guidelines in the rubric. Our hope is that you will later turn this proposed activity into a real-world grant proposal with a methodologically sound power and sample size analysis. Our final course assessment is a final examination in the course. This examination is a short test of conceptual knowledge you gained in the course. We strongly encourage you to complete the final examination only after completing all other assessment activities in the course. You should allocate approximately four to six hours each week for the five week period to successfully complete the course. Again, it is suggested that you complete the course activities in the prescribed order to ensure mastery of the learning objectives. Whatever your motivation, we hope this course will help in your academic journey and professional career. Again, I look forward to working with you over the next five weeks, this should be a fun learning experience.
