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BPS - 5th Ed. Chapter 91 Producing Data: Experiments.

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1 BPS - 5th Ed. Chapter 91 Producing Data: Experiments

2 BPS - 5th Ed. Chapter 92 How Data are Obtained u Observational Study –Observes individuals and measures variables of interest but does not attempt to influence the responses –Describes some group or situation –Sample surveys are observational studies u Experiment –Deliberately imposes some treatment on individuals in order to observe their responses –Studies whether the treatment causes change in the response.

3 BPS - 5th Ed. Chapter 93 Experiment versus Observational Study Both typically have the goal of detecting a relationship between the explanatory and response variables. u Experiment –create differences in the explanatory variable and examine any resulting changes in the response variable (cause-and-effect conclusion) u Observational Study –observe differences in the explanatory variable and notice any related differences in the response variable (association between variables)

4 BPS - 5th Ed. Chapter 94 Why Not Always Use an Experiment? u Sometimes it is unethical or impossible to assign people to receive a specific treatment. u Certain explanatory variables, such as handedness or gender, are inherent traits and cannot be randomly assigned.

5 BPS - 5th Ed. Chapter 95 Confounding u The problem: –in addition to the explanatory variable of interest, there may be other variables (explanatory or lurking) that make the groups being studied different from each other –the impact of these variables cannot be separated from the impact of the explanatory variable on the response

6 BPS - 5th Ed. Chapter 96 Confounding u The solution: –Experiment: randomize experimental units to receive different treatments (possible confounding variables should “even out” across groups) –Observational Study: measure potential confounding variables and determine if they have an impact on the response (may then adjust for these variables in the statistical analysis)

7 BPS - 5th Ed. Chapter 97 Question A recent newspaper article concluded that smoking marijuana at least three times a week resulted in lower grades in college. How do you think the researchers came to this conclusion? Do you believe it? Is there a more reasonable conclusion?

8 BPS - 5th Ed. Chapter 98 Case Study The Effect of Hypnosis on the Immune System reported in Science News, Sept. 4, 1993, p. 153

9 BPS - 5th Ed. Chapter 99 Case Study The Effect of Hypnosis on the Immune System Objective: To determine if hypnosis strengthens the disease-fighting capacity of immune cells.

10 BPS - 5th Ed. Chapter 910 Case Study u 65 college students –33 easily hypnotized –32 not easily hypnotized u white blood cell counts measured u all students viewed a brief video about the immune system

11 BPS - 5th Ed. Chapter 911 Case Study u Students randomly assigned to one of three conditions –subjects hypnotized, given mental exercise –subjects relaxed in sensory deprivation tank –control group (no treatment)

12 BPS - 5th Ed. Chapter 912 Case Study u white blood cell counts re-measured after one week u the two white blood cell counts are compared for each group u results –hypnotized group showed larger jump in white blood cells –“easily hypnotized” group showed largest immune enhancement

13 BPS - 5th Ed. Chapter 913 Case Study The Effect of Hypnosis on the Immune System Is this an experiment or an observational study?

14 BPS - 5th Ed. Chapter 914 Case Study The Effect of Hypnosis on the Immune System Does hypnosis and mental exercise affect the immune system?

15 BPS - 5th Ed. Chapter 915 Case Study Weight Gain Spells Heart Risk for Women “Weight, weight change, and coronary heart disease in women.” W.C. Willett, et. al., vol. 273(6), Journal of the American Medical Association, Feb. 8, (Reported in Science News, Feb. 4, 1995, p. 108)

16 BPS - 5th Ed. Chapter 916 Case Study Objective: To recommend a range of body mass index (a function of weight and height) in terms of coronary heart disease (CHD) risk in women. Weight Gain Spells Heart Risk for Women

17 BPS - 5th Ed. Chapter 917 Case Study u Study started in 1976 with 115,818 women aged 30 to 55 years and without a history of previous CHD. u Each woman’s weight (body mass) was determined. u Each woman was asked her weight at age 18.

18 BPS - 5th Ed. Chapter 918 Case Study u The cohort of women were followed for 14 years. u The number of CHD (fatal and nonfatal) cases were counted (1292 cases). u Results were adjusted for other variables (smoking, family history, menopausal status, post-menopausal hormone use).

19 BPS - 5th Ed. Chapter 919 Case Study u Results: compare those who gained less than 11 pounds (from age 18 to current age) to the others. –11 to 17 lbs: 25% more likely to develop heart disease –17 to 24 lbs: 64% more likely –24 to 44 lbs: 92% more likely –more than 44 lbs: 165% more likely

20 BPS - 5th Ed. Chapter 920 Case Study Is this an experiment or an observational study? Weight Gain Spells Heart Risk for Women

21 BPS - 5th Ed. Chapter 921 Case Study Does weight gain in women increase their risk for CHD? Weight Gain Spells Heart Risk for Women

22 BPS - 5th Ed. Chapter 922 Explanatory and Response Variables u a response variable measures what happens to the individuals in the study u an explanatory variable explains or influences changes in a response variable u in an experiment, we are interested in studying the response of one variable to changes in the other (explanatory) variables.

23 BPS - 5th Ed. Chapter 923 Experiments: Vocabulary u Subjects –individuals studied in an experiment u Factors –the explanatory variables in an experiment u Treatment –any specific experimental condition applied to the subjects; if there are several factors, a treatment is a combination of specific values of each factor

24 BPS - 5th Ed. Chapter 924 Case Study Effects of TV Advertising Rethans, A. J., Swasy, J. L., and Marks, L. J. “Effects of television commercial repetition, receiver knowledge, and commercial length: a test of the two-factor model,” Journal of Marketing Research, Vol. 23 (1986), pp

25 BPS - 5th Ed. Chapter 925 Case Study Objective: To determine the effects of repeated exposure to an advertising message (may depend on length and how often repeated) Effects of TV Advertising

26 BPS - 5th Ed. Chapter 926 Case Study u subjects: a certain number of undergraduate students u all subjects viewed a 40-minute television program that included ads for a digital camera

27 BPS - 5th Ed. Chapter 927 Case Study u some subjects saw a 30-second commercial; others saw a 90-second version u same commercial was shown either 1, 3, or 5 times during the program u there were two factors: length of the commercial (2 values), and number of repetitions (3 values)

28 BPS - 5th Ed. Chapter 928 Case Study u the 6 combinations of one value of each factor form six treatments Factor B: Repetitions 1 time3 times5 times Factor A: Length 30 seconds seconds 456 subjects assigned to Treatment 3 see a 30-second ad five times during the program

29 BPS - 5th Ed. Chapter 929 Case Study u after viewing, all subjects answered questions about: recall of the ad, their attitude toward the camera, and their intention to purchase it – these were the response variables.

30 BPS - 5th Ed. Chapter 930 Comparative Experiments u Experiments should compare treatments rather than attempt to assess the effect of a single treatment in isolation u Problems when assessing a single treatment with no comparison: –conditions better or worse than typical v lack of realism (potential problem with any expt) –subjects not representative of population –placebo effect (power of suggestion)

31 BPS - 5th Ed. Chapter 931 Randomized Comparative Experiments u Not only do we want to compare more than one treatment at a time, but we also want to make sure that the comparisons are fair: randomly assign the treatments –each treatment should be applied to similar groups or individuals (removes lurking vbls) –assignment of treatments should not depend on any characteristic of the subjects or on the judgment of the experimenter

32 BPS - 5th Ed. Chapter 932 Experiments: Basic Principles u Randomization –to balance out lurking variables across treatments u Placebo –to control for the power of suggestion u Control group –to understand changes not related to the treatment of interest

33 BPS - 5th Ed. Chapter 933 Randomization: Case Study Quitting Smoking with Nicotine Patches (JAMA, Feb. 23, 1994, pp ) u Variables: –Explanatory: Treatment assignment –Response: Cessation of smoking (yes/no) u Treatments –Nicotine patch –Control patch u Random assignment of treatments

34 BPS - 5th Ed. Chapter 934 Placebo: Case Study Quitting Smoking with Nicotine Patches (JAMA, Feb. 23, 1994, pp ) u Variables: –Explanatory: Treatment assignment –Response: Cessation of smoking (yes/no) u Treatments –Nicotine patch –Placebo: Control patch u Random assignment of treatments

35 BPS - 5th Ed. Chapter 935 Control Group: Case Study Mozart, Relaxation and Performance on Spatial Tasks (Nature, Oct. 14, 1993, p. 611) u Variables: –Explanatory: Relaxation condition assignment –Response: Stanford-Binet IQ measure u Active treatment: Listening to Mozart u Control groups: –Listening to relaxation tape to lower blood pressure –Silence

36 BPS - 5th Ed. Chapter 936 Completely Randomized Design u In a completely randomized design, all the subjects are allocated at random among all of the treatments. –can compare any number of treatments (from any number of factors)

37 BPS - 5th Ed. Chapter 937 Statistical Significance u If an experiment (or other study) finds a difference in two (or more) groups, is this difference really important? u If the observed difference is larger than what would be expected just by chance, then it is labeled statistically significant. u Rather than relying solely on the label of statistical significance, also look at the actual results to determine if they are practically important.

38 BPS - 5th Ed. Chapter 938 Double-Blind Experiments u If an experiment is conducted in such a way that neither the subjects nor the investigators working with them know which treatment each subject is receiving, then the experiment is double-blinded –to control response bias (from respondent or experimenter)

39 BPS - 5th Ed. Chapter 939 Double-Blinded: Case Study Quitting Smoking with Nicotine Patches (JAMA, Feb. 23, 1994, pp ) u Variables: –Explanatory: Treatment assignment –Response: Cessation of smoking (yes/no) u Double-blinded –Participants don’t know which patch they received –Nor do those measuring smoking behavior

40 BPS - 5th Ed. Chapter 940 (not) Double-Blinded: Case Study Mozart, Relaxation and Performance on Spatial Tasks (Nature, Oct. 14, 1993, p. 611) u Variables: –Explanatory: Relaxation condition assignment –Response: Stanford-Binet IQ measure u Not double-blinded –Participants know their treatment group u Single-blinded –Those measuring the IQ

41 BPS - 5th Ed. Chapter 941 Pairing or Blocking u Pairing or blocking –to reduce the effect of variation among the subjects –different from a completely randomized design, where all subjects are allocated at random among all treatments

42 BPS - 5th Ed. Chapter 942 Matched Pairs Design u Compares two treatments u Technique: –choose pairs of subjects that are as closely matched as possible –randomly assign one treatment to one subject and the second treatment to the other subject u Sometimes a “pair” could be a single subject receiving both treatments –randomize the order of the treatments for each subject

43 BPS - 5th Ed. Chapter 943 Block Design u A block is a group of individuals that are known before the experiment to be similar in some way that is expected to affect the response to the treatments. u In a block design, the random assignment of individuals to treatments is carried out separately within each block. –a single subject could serve as a block if the subject receives each of the treatments (in random order) –matched pairs designs are block designs

44 BPS - 5th Ed. Chapter 944 Pairing or Blocking: Case Study Mozart, Relaxation and Performance on Spatial Tasks (Nature, Oct. 14, 1993, p. 611) u Variables: –Explanatory: Relaxation condition assignment –Response: Stanford-Binet IQ measure u Blocking –Participants practiced all three relaxation conditions (in random order). Each participant is a block. –IQ’s re-measured after each relaxation period

45 BPS - 5th Ed. Chapter 945 Pairing or Blocking: Case Study Quitting Smoking with Nicotine Patches (JAMA, Feb. 23, 1994, pp ) u Variables: –Explanatory: Treatment assignment –Response: Cessation of smoking (yes/no) u Pairing? –Cannot block: participants can only take one treatment –Could use a matched-pairs design (pair subjects based on how much they smoke)

46 BPS - 5th Ed. Chapter 946 u Compare effectiveness of three television advertisements for the same product, knowing that men and women respond differently to advertising. –Three treatments: ads (need three groups) –Two blocks: men and women Pairing or Blocking: Example from Text Men, Women, and Advertising

47 BPS - 5th Ed. Chapter 947 Pairing or Blocking: Example from Text Men, Women, and Advertising


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