Preparing for the 2 nd Hourly

What is an hourly? An hourly is the same thing as an in-class test. How many problems will be on the hourly? There will be four cases on the hourly, and you will work all four of them. What will the cases look like? The cases will be similar to cases that you have worked in class, and will be similar to cases from previous versions of the second hourly.

Will the problems count equally? Yes. There will be four (4) cases, at 25 points Maximum per case, for a total of 100 points maximum. Will there be partial credit? Yes, but be aware that full work and detail is required for full credit. Your work and details are the basis for scoring each case solution. What about the testing protocol and tool-sheet? The hourly is not a memory test. Hence, you are permitted the use of one (1) 8.5” by 11” sheet of paper. Put on this sheet whatever it is that you deem useful. You alone will use this sheet. Sign and abide by the test protocol that will accompany the hourly. What about the calculator? You must provide your own working calculator, and you must be able to use this calculator. Do not share calculators. Your calculator is your individual responsibility.

The Essential Randomized, Controlled, Blinded Clinical Trial The clinical trial as discussed in this course is a very simplified version of those designed and executed in the Real World. The method essentially requires the following: A Well Defined Disease or Condition of Interest An Appropriate Population at Risk A Set of Well Defined Treatments A Set of Well Defined End Points or Outcomes A Random Method for Assigning Subjects to Treatments A Method of Obtaining Informed Consent from Potential Subjects Implementation of a Double Blind We briefly sketched a variety of these simplified clinical trials. Examples of these are available online.

A few notes of clarification. The essential purpose of randomization is to assign subjects to treatments in such a way that the only systematic differences between treatment groups are random variations and the treatments themselves. Blinding of both subjects and clinic workers is employed to avoid differences in recorded responses due to either placebo effect or observer bias. Blinding also helps to avoid excessive subject loss when a placebo is employed. A placebo is a medically inert mock treatment, intended to resemble as closely as possible the active treatments in a study. Broad classes of study end points and outcomes include treatment effect in modifying disease or condition, survival/mortality, quality of life, side effects and adverse events.

The Essential Random Sample Survey The random sample survey was discussed in our class as a method for scientifically obtaining information in a representative manner from a population of interest. We presented some general principles on the design an execution of credible scientific polling. Our simplified design for a random sample survey included: A Well Defined Population of Interest A Sampling Frame Based on the Population of Interest A Random Sample Obtained from the Sampling Frame A Reasonable Set of Research Objectives A Well Defined Survey Instrument Based on the Research Objectives A Reasonable Protocol for Administering the Survey Instrument

Design Fault Spot In this case type, brief descriptions of clinical trials or sample surveys are presented. Briefly identify problems with these designs.

Describing a Sample – Descriptive Statistics In many applications, it can be difficult to determine what it is that a sample is trying to tell us. A sample may have many variables; some useful, some not, some reliable, some not. A sample may be large, with many observations; hence requiring summarization. The descriptive statistic summarizes an entire sample, and the form of the statistic yields a particular kind of information about a sample. Statistics that we examined include: Mean Median Minimum Maximum Percentiles/Quartiles Standard Deviation Inter-quartile Differences Range Inter-quartile Range Taken collectively, these sample statistics can yield an effective summary of the sample.

Describing a Sample – Summary Intervals The advantage of the above statistics is their breadth and variety – they can tell a complete story about a sample of data. However, taken collectively, there are many of these statistics, and a briefer summary may be desired. Summary intervals provide a two-number summary, with very simple accompanying interpretations. They take the form: [ m-k*sd, m+k*sd ]; and their precise interpretation depends upon the nature of the sample being summarized, and the numerical value of the parameter k. The two rules used in this class were the Empirical Rule and Tchebysheff’s Inequalities.

Notes for Study / Preparation Study for one case type at a time. Take notes as you go along. When you have finished study for all four case types, compile your notes into a single tool sheet. Customize this tool sheet for your own personal use.

How to prepare for the 2 nd Hourly Two levels of work for each case: Computation, Writing. In some of the cases, there is much of both. Be sure that you have the computing and writing under control. Be sure that you can work the in-class cases, and the cases on the old tests. I may exclude certain cases if I deem them too involved, too lengthy or no longer of interest.

Preparing the Tool Sheet Suppose that you knew in advance that you were going to blank out on the test… What would you need to recover? Put these things on your tool sheet.

Writing is Important! In the numerical cases, interpretation and discussion will account for 40% of the points. In the non-numerical cases, writing will account for 100% of the points. Be sure that you can write the cases in accordance with established standards, as published in case summaries and previous second hourlies.

Problem Tasks Clinical Trial Design Sketch Sketch Clinical Trials Briefly and Completely Design Spot Fault Spot Faults in Clinical Trials Based on Brief Descriptions of Designs Spot Faults in Sample Survey Designs Based on Brief Descriptions of Designs Descriptive Statistics Edit Data provided in cases Compute Statistics Using the Calculator Interpret Statistics Briefly and Completely Summary intervals Edit Data provided in cases Compute Intervals Using the Calculator Interpret Intervals Briefly and Completely