independent variables
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A two-factor study is a research study that has two :
a) treatment groups b)independent variables
Two factorial design is one involving two factors in a single experiment
Two factors are independent variables not between treatment groups.
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- 7. While age is not considered to be a variable of interest, there is some concern that older people may react differently to the treatments than younger people. The best way to address this concern is to design the study to make use of: a. Blinding b. Randomization c. Blocking d. Replication11) Consider each of the following scenarios and state whether the variable in question is a confounder, or whether more information is needed to assess confounding. Choose from Yes / No / or Need more information, and provide a very brief explanation for your selection a) In a cohort study of liver cancer among males, incidence rates of liver cancer among men with unhealthy alcohol use are compared to incidence rates of liver cancer among non-drinkers. Is gender a confounder in this study? b) A case-control study of the risk of beer consumption and oral cancer among men (overall OR = 2.8). In this study, cigarette smoking is associated with beer consumption and is a risk factor for oral cancer among both beer drinkers (OR=3.6) and nondrinkers (OR=3.7). Is cigarette smoking a confounder in this study? c) In a study of the risk of pulmonary hypertension among women who take diet drugs to lose weight, the crude relative risk of pulmonary hypertension comparing diet drug users to…2. An article in the journal Applied Nutritional Investigation reported the results of a comparison of two different weight-loss programs (Liao, 2007). In the study, obese participants were randomly assigned to one of two groups and the percent of body fat loss was recorded. The soy group, a low-calorie group that ate only soy-based proteins (M= 3.1, s=0.55), while the traditional group, a low-calorie group that received 2/3 of their protein from animal products and 1/3 from plant products (M= 1.9, s=0.45). If sm1-M2 = 0.24, s²pooled = 0.25, n1 = 8, n2 = 10 is there a difference between the two diets. Use alpha of .05 and a two-tailed test to complete the 4 steps of hypothesis testing.
- 7) The following results are from data that were collected from a sample of Chicago Cubs baseball games. The dependent variable is ATTENDANCE, TEMP is a variable measuring the forecasted game-time temperature: WIN% is a variable measuring the winning percentage of the Cubs before the game is played, OPWIN% is a variable measuring the winning percentage of their opponent, WEEKEND is a dummy variable = 1 if the game is played on a weekend and = 0 if the game is played during a weekday, PROMOTION is a dummy variable = 1 if there is a promotion for the game (giving away something to those who attend the game) and = 0 if there is not a promotion, and WEEK*PROM is an interaction term equal to WEEKEND*PROMOTION. a) What is the predicted attendance if TEMP = 70, WIN% = 500, OPWIN% = 500, the game is played on a weekend and there is NO promotion? b) What is the predicted attendance if TEMP = 70, WIN% = 500, OPWIN% = 500, the game is played on a weekend and there is a promotion? c) Based on…Study 2: Pill Appearance and Perceived Pain. Does the shape or color of a pain pill influence its effectiveness? Although logically it shouldn’t, whether we believe a drug will work does have a powerful effect on our perceptions (e.g., placebo effect). In this experiment, 4 groups of adult patients were given the same amount of Advil after dental surgery for pain relief, but the color and shape of the pill varied. Researchers hypothesized that an unusual shape or color would lead people to believe the pills were new and special and thus would expect them to be more effective than common round, white pills. Researchers also wanted to know if there is an interaction between shape and color Data Labels ShapePill {1=Round; 2=Diamond} ColorPill {1=White; 2=BlueGreen} Gender {0=Woman; 1=Man; 2=Nonbinary person) Descriptions of the Variables and Descriptive Statistics: Referring to the JASP output, and using sentences, present the descriptive statistics of each group: for example:…A group of 600 patients who suffer from seasonal allergies is asked to participate in a study to determine the effectiveness of a new medication. The patients are divided randomly into two groups, one was given the actual medication and one received a placebo pill. After 2 months of treatment, 64% of the patients who took the medication had fewer allergy symptoms, while only 36% of those who took the placebo had fewer allergy symptoms. a. What is the treatment variable? b. What is the response (or outcome) variable? c. Was this an observational study or a controlled experiment? Explain how you know. d. Assuming the rest of the study was well-designed, use your answers to discuss whether it would be reasonable to conclude that taking the new medication caused fewer allergy symptoms.
- A study prospectively examined whether sleep-disordered breathing was associated with an increased risk of death from any cause in a cohort of 600 adults participating in the Sleep Heart Health Study. Study participants were classified into four groups depending on the extent of their sleep-disordered breathing (none, mild, moderate, or severe). The counts of deaths over the course of the study are reported for each group in the following two-way table. Mild Severe 100 Death No Death Total None 40 100 140 40 100 140 Moderate 20 100 120 Total 200 400 600 100 200 We want to know whether the study findings give evidence of a significant difference of the number of deaths between the different groups. Set up the alternative hypothesis (H, : The distribution of the categorical variable is not as given by the null hypothesis (lack of fit) At least ones of the means is different from the others O The two categorical variables are dependent The distribution of the categorical variable is not…A study prospectively examined whether sleep-disordered breathing was associated with an increased risk of death from any cause in a cohort of 600 adults participating in the Sleep Heart Health Study. Study participants were classified into four groups depending on the extent of their sleep-disordered breathing (none, mild, moderate, or severe). The counts of deaths over the course of the study are reported for each group in the following two-way table. Death No Death Total None 40 100 140 Mild 40 100 140 Moderate 20 100 120 Severe 100 100 200 Total 200 400 600 We want to know whether the study findings give evidence of a significant difference of the number of deaths between the different groups. The observed test statistic is 3.610 42.857 5.476 8.075Among the literature on quitting smoking are data detailing the relative successfulness of people of different ages in quitting smoking. A study of 400 adults who began various smoking-cessation programs produced the data in the table below. In the table, each participant is classified according to two variables: length of their smoking cessation period ("Less than two weeks", "Between two weeks and one year", or "At least one year") and age ("21-34", or "35 and over"). In the table, "less than two weeks" means that the individual returned to smoking within two weeks of beginning the program; "between two weeks and one year" means that the individual lasted the first two weeks without smoking but retuned to smoking within a year; and "at least one year" means that the individual has not smoked for at least a year since beginning the program. The table is a contingency table whose cells contain the respective observed frequencies of classifications of the 400 smokers. In addition, three…
