For the port-wine stains research study, do the following: a. Describe how the subjects in this

For the port-wine stains research study, do the following:...

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Key Concepts

Randomization

Randomization is a key concept in experimental design that involves selecting or assigning study subjects in such a way that each individual has an equal chance of being included and placed into any group. This process minimizes selection bias and helps ensure that any differences observed between groups are due to the intervention rather than extraneous factors. It encompasses both random sampling from a population and random assignment to different experimental conditions.

Research Hypotheses

Research hypotheses are specific, testable predictions about the expected outcomes of a study based on theoretical understanding or prior evidence. They guide the experimental design and analysis by framing the key relationships or differences the researchers intend to explore. Clearly stating multiple hypotheses allows for the examination of various potential effects or associations, providing a structured approach to investigating the impact of the intervention or treatment under study.

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What design? Analyze the design of each research example reported. Is it a sample survey, an observational study, or an experiment? If a sample, what are the population, the parameter of interest, and the sampling procedure? If an observational study, was it retrospective or prospective? If an experiment, describe the factors, treatments, randomization, response variable, and any blocking, matching, or blinding that may be present. In each, what kind of conclusions can be reached? An artisan wants to create pottery that has the appearance of age. He prepares several samples of clay with four different glazes and test fires them in a kiln at three different temperature settings.

read-each-brief-report-of-statistical-research-and-identify-a-whether-it-was-an-observational-stu-25

Read each brief report of statistical research, and identify a) whether it was an observational study or an experiment. If it was an observational study, identify (if possible) b) whether it was retrospective or prospective. c) the subjects studied and how they were selected. d) the parameter of interest. e) the nature and scope of the conclusion the study can reach. If it was an experiment, identify (if possible) b) the subjects studied. c) the factor(s) in the experiment and the number of levels for each. e) the response variable measured. f) the design (completely randomized, blocked, or matched). g) whether it was blind (or double-blind). h) the nature and scope of the conclusion the experiment can reach. Some people claim they can get relief from migraine headache pain by drinking a large glass of ice water. $\mathrm{Re}$ searchers plan to enlist several people who suffer from migraines in a test. When a participant experiences a migraine headache, he or she will take a pill that may be a standard pain reliever or a placebo. Half of each group will also drink ice water. Participants will then report the level of pain relief they experience.

An area of research in biomechanics and gerontology concerns falls and fall-related injuries, especially for elderly people. Recent studies have focused on how individuals respond to large postural disturbances (e.g., tripping, induced slips). One question is whether subjects can be instructed to improve their recovery from such disturbances. Suppose researchers want to compare two such recovery strategies, lowering (quickly stepping down with front leg and then raising back leg over the object) and elevating (lifting front leg over the object). Subjects will have first been trained on one of these two recovery strategies, and they will be asked to apply it after they feel themselves tripping. The researchers will then induce the subject to trip while walking (but harnessed for safety) using a concealed mechanical obstacle. Suppose the following 24 subjects have agreed to participate in such a study: Females: Alisha, Alice, Betty, Martha, Audrey, Mary, Barbie, Anna Males: Matt, Peter, Shawn, Brad, Michael, Kyle, Russ, Patrick, Bob, Kevin, Mitch, Marvin, Paul, Pedro, Roger, Sam 1a. One way to design this study would be to assign the 8 females to use the elevating strategy and the 16 males to use the lowering strategy. Would this be a reasonable strategy? Why not? 1b. One way to deal with this issue is to assign 4 females and 8 males to each group. Show how the proportion of males in each group is the same. 1c. Now, if you saw a difference in the proportion of trips in the two groups, could it be because of the sex of the subject? Why or why not? Could it be due to other variables, distinct from the recovery strategy? Why or why not? 1d. Because there will always be more potential confounding variables which could be distributed unevenly between the groups being compared, identify a better method for deciding who uses which strategy. 1e. Let's explore the process of random assignment to determine whether it does "work." First, let's focus on the sex (male vs. female) variable. Suppose we put each person's name on a slip, put those slips in a hat and mix them up thoroughly, and then randomly draw out 12 slips for names of people to assign to the elevating strategy. What proportion of this group do you expect will be male? What proportion of the lowering strategy do you expect will be male? Do you think we will always get an 8/8 split (8 males in each treatment group)? 1f. To repeat this random assignment a large number of times to observe the long-run behavior, we will use the Randomizing Subjects applet. Open the applet and press the Randomize button. What proportion of subjects assigned to Group 1 are men? Of Group 2? What is the difference in these two proportions? 1g. Press the Randomize button again. Was the difference in proportions of men the same this time? 1h. Change the number of replications from 1 to 198 (for 200 total), uncheck the Animate option, and press the Randomize button. The dotplot will display the difference between the two proportions of men for each of the 200 repetitions of the random assignment process. Where are these values centered? 1i. Does random assignment always equally distribute/balance the men and women between the two groups? Is there a tendency for there to be a similar proportion of men in the two groups? Explain. 1j. Prior research has also shown that the likelihood of falling is related to variables such as walking speed, stride rate, and height, so we would like the random assignment to distribute these variables equally between the groups as well. In the applet, use the pull-down menu to switch from the sex-of-participant variable to the height variable. The dotplot now displays the differences in average height between Group 1 and Group 2 for these 200 repetitions. In the long run, does random assignment tend to equally distribute the height variable between the two groups? Explain how you are deciding. 1k. Suppose there is a "balance gene" that is related to people's ability to recover from a trip. We didn't know about this gene ahead of time, but if you select the Reveal gene? button and then select gene from the pull-down menu, the applet shows you this gene information for each subject and also how the proportions with the gene differ in the two groups. Does this variable tend to equalize between the two groups in the long run? Explain. 1l. Suppose there were other "x-variables" that we could not measure such as stride rate or walking speed. Select the Reveal both? button and use the pull-down menu to display the results for the x-variable (X-var). Does random assignment generally succeed in equalizing this variable between the two groups or is there a tendency for one group to always have higher results for the x-variable? Explain. 1m. Suppose this study finds a statistically significant difference between the two groups. What conclusion would you draw? For what population? What additional information would you need to know? 1n. As in #1m, if you obtain a statistically significant result, what does that suggest about the potential for a cause-and-effect relationship? Why?

Transcript

00:01 Some people claim that they can get relief from migraine headache pain by drinking a large glass of ice water.

00:05 Researchers plan to enlist several people who suffer from migraines in a test.

00:09 When a participant receives or experiences, a migraine headache, he or she will take a pill.

00:14 That may be a standard pain reliever or a placebo.

00:16 Half of each group will also drink ice water.

00:19 Participants will then report the level of pain relief they experience.

00:24 This is an experiment because people in different groups are getting different treatments.

00:29 The subjects are people suffering from migraines.

00:47 The factors are the, i'll call it the standard pain relief pill...

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