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Critique Format; Hypothesis testing; Student s t test; Nonparametric statistics

Format of the Final Paper. Components. Your clinical question and how you developed it.5-8 article reviews - use Law format; include level of evidence on EACH review; include each articleIn the paper itself, summarize strengths and weaknesses using each of Law's categories across all articles, I

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Critique Format; Hypothesis testing; Student s t test; Nonparametric statistics

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    1. Critique Format; Hypothesis testing; Student’s t test; Nonparametric statistics OT 667 - Class 6

    2. Format of the Final Paper

    3. Components Your clinical question and how you developed it. 5-8 article reviews - use Law format; include level of evidence on EACH review; include each article In the paper itself, summarize strengths and weaknesses using each of Law’s categories across all articles, I.e. sample, designs, outcome measures, intervention, etc. Include a summary of levels of evidence too!

    4. More on final paper…. Discuss the problems with the evidence you reviewed - levels, small samples, outcomes measures, etc. Discuss what you learned and how it addressed (or didn’t address) the clinical question you started with. If you had to change your question after you started looking, discuss that briefly too.

    5. And then…. Consider how you would use the evidence you found clinically. (we will discuss this in class further) Last of all, what did doing this paper teach you? Remember APA format, remember to cite when you use direct quotes, include a title page which has all group members names on it

    6. Probability Chance of something happening… Statistically, probability is a means of predicting an outcome… A system of rules for analyzing a possible set of outcomes…. Flipping a coin, rolling the dice….

    7. ..more on probability The likelihood that any one event will occur, given all the possible outcomes.. The probability something should happen, not the probability it will happen! Probability is used as a guideline… What is the probability you will receive a desired grade???

    8. Hypothesis Testing Is judged by indicating the probability level we expect the outcome of an experiment will occur….. so many times out of one hundred….. Usually indicated as p (probability) = .05 Setting the probability level is also called setting the alpha level of an experiment...

    9. Hypothesis testing defined A method for deciding if an observed effect or result occurs by chance alone OR if we can argue the results found actually happened as a result of an intervention.

    10. The Null Hypothesis In order to decide if the results of an experiment occur by chance or if the effects seen are the result of a treatment, researchers declare a null hypothesis (Ho) and a research hypothesis (Ha).

    11. The null hypothesis states that there will be NO DIFFERENCE between groups as a result of the treatment.

    12. The research hypothesis states there WILL BE a significant difference in the outcomes between groups as a result of the treatment.

    13. To test a hypothesis, researchers talk about “rejecting the null” in order to demonstrate the treatment has an effect.

    14. When you reject the null, you say that there IS a significant difference between the groups, indicating the treatment was effective.

    15. When you ACCEPT the null, you are saying there is no difference in the outcomes of a treatment

    16. Whether you accept or reject the null is based on whether the outcome of a statistical test is greater or less than the proposed alpha level, usually .05

    17. For instance, when the results of a statistical test come out at the .056 alpha level, would you accept or reject the null??? Your actual alpha level is .05 - that is, 5 times out of 100 your results are due to chance The .056 means that 6 times out of a hundred, the results of a study would be due to chance….

    18. Direction of a statistical question Research questions traditionally are asked in 2 ways 1) NDT treatment will result in better outcomes than SI treatment OR 2) There will be a difference between outcomes of NDT and SI treatment

    19. The “tail” of a question One-tailed questions - that is, one intervention will result in a better outcome- are more powerful and more difficult to demonstrate Two-tailed questions - those questions there will be a difference between treatments but don’t say which one will be better - are called two-tailed questions

    20. Dynamic splints will result in better functional outcomes than static splints There will be a change in play behaviors as a result of parent education intervention vs direct child intervention Sensory integration treatment will result in better academic performance than perceptual motor treatment

    21. The story of the tails.. Statistically, one-tailed tests result in a critical value which is compared to values at the positive end of the normal curve called the critical region The critical values of two-tailed tests are compared to values in a critical region at either positive or negative end of the normal curve

    22. One-tailed tests are regarded as more powerful because there is less chance of a significant difference between 2 groups

    23. The direction of a question is specified at the prior to statistical analysis and cannot be changed once the data analysis begins. So you had BETTER be sure of the outcomes when you ask a one-tailed question...

    24. There is a risk for error in statistical testing. There are two kinds of error…..

    25. Type 1 Error When you make a Type 1 error, you reject a null hypothesis and say there IS a difference between 2 groups when in fact there is NO difference. The convention of setting the level of significance or alpha level at .05 means the researcher can make a Type 1 error 5 times out of 100

    26. Be careful with levels of significance…. The p value should not be used to indicate the validity of the outcome of a study. If your experiment results in a p value of .001, it only supports a relative degree of confidence in the decision to reject the null

    27. Type II Error The risk of accepting a null that is false. That means that you say that the results of a study are NOT significant when, in fact, they are.

    28. Statistical Power Statistical power is the probability that a test will lead to rejecting the null (saying there IS a difference). The more powerful a test, the less likely you are to make a Type II error.

    29. Items that affect power Variance of a sample (the lower the variance, the more powerful a test) The significance criterion (alpha level) Sample Size (the bigger the better) Effect size (the effectiveness of the independent variable)

    30. Student’s t test

    31. What is the t test? A parametric statistical test which analyzes the difference between the means of scores between two groups. There are assumptions that need to be considered when using the t-test. These are the data is normally distributed the variances are homogenous or similar the groups are of equal size

    32. The research question asked by the t test “Is there a difference between the two groups?”

    33. Two kinds of t tests t test for paired samples - when the subjects are measured on a variable, receive the treatment, then measured again. The pre and post-test means of the measures are compared t test for independent samples - comparison of means between 2 different groups after a treatment is administered

    34. Multiple t tests When you read a study where several t tests are used to test the same data, BEWARE… For example, a researcher writes an article on the outcomes of a treatment used in persons with dementia. More than one measure is used to study the outcome. This means the risk of committing a Type I error (rejecting a true null or finding a difference when there isn’t one) is increased.

    35. Solutions for the problem Perform an ANOVA Adjust the alpha level using a Bon Ferroni correction - to do this you half or lower the alpha level

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