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Chapter 9: Problem 49

Quick randomizing. Here's a quick and easy way to randomize. You have 100 subjects: 50 women and 50 men. Toss a coin. If it's heads, assign all the men to the treatment group and all the women to the control group. If the coin comes up tails, assign all the women to treatment and all the men to control. This gives every individual subject a \(50-50\) chance of being assigned to treatment or control. Why isn't this a good way to randomly assign subjects to treatment groups?

Short Answer

Expert verified
It's not good because assignments are gender-linked, not truly individual or independent.

Step by step solution

01

Understanding Randomization

Randomization in experiments is used to eliminate bias when assigning subjects to treatment groups. It's considered fair if each subject has an independent and equal probability of being assigned to any group.
02

Analysis of Given Method

In this method, a coin flip determines the treatment group assignments of all subjects within a gender. Each subject has a 50% chance of being in a particular group based on the coin flip, but it is not independent since the outcome is the same for all subjects of the same gender.
03

Identifying Bias

The method introduces bias because the group assignment is not truly random for individuals. The group assignments are pre-determined by gender once the coin is flipped, leading to a lack of independence in individual assignments.
04

Evaluation of Independence

True randomization requires each individual's assignment to be independent of others. This method does not achieve that since the result of the coin flip affects all subjects within a gender group.
05

Conclusion on Randomization Quality

The described method is not a good way to randomize because it does not provide equal, independent random assignment for each individual; it instead links the results for all subjects within the same gender based on a single event.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Bias in Experimental Design
Bias in experimental design occurs when certain factors systematically affect the results or interpretations in a study, leading to skewed or inaccurate outcomes.
In the given method where a coin is used to assign groups, bias creeps in because the flipping result applies not to individuals, but to predefined groups (men and women).
  • For instance, the coin determines the fate of all members of one gender at once, which is not ideal for fair randomization.
  • This "block assignment" based on gender results in biased outcomes, meaning that the differences observed may be more related to the gender rather than the treatment effect.
  • The lack of individual randomness could lead to confounding variables, where other factors like gender characteristics actually drive the results.
To avoid bias, it's crucial to ensure that the treatment groups are formed purely by chance, not through predetermined criteria like gender. Ensuring that each subject has an independent chance of assignment can help in reducing bias and obtaining reliable, generalizable results.
Independent Probability
Independent probability in experimental design refers to the concept that the group assignment of any one subject should not be influenced by the assignment of any other subject.
In the provided method, although every person has a 50% probability of being in the treatment or control group, this probability is not independent because of the reliance on the coin flip's outcome for each gender.
  • For true randomness, each subject's assignment must be made without regard to others' assignments.
  • This assures that the probabilities are not linked across subjects, eliminating factors that might introduce additional bias.
Independent probability is crucial as it ensures that external influences do not alter the random process. This keeps the experiment fair and the results unbiased, allowing the experimental outcomes to be attributed solely to the treatment and not the process of assigning treatment.
Treatment Group Assignment
Treatment group assignment is a fundamental part of experimental design where subjects are allocated to different interventions or control groups.
The optimal process involves assigning each participant to a group randomly and independently.
  • This ensures each subject has an equal opportunity to be in any group, preventing systematic differences between groups at the outset of the study.
  • Random assignment helps create comparable groups, which is vital for interpreting the effects of the treatment accurately.
The method used in the exercise fails this ideal because it uses gender to determine group assignment once the coin is flipped.
  • Rather than allocating individuals by chance, entire groups (men or women) are assigned based on a single event, contrasting with the goal of creating balanced groups through randomness.
  • For effective treatment group assignment, more sophisticated randomization methods, such as simple random sampling or stratified sampling, can be used to maintain balance and fairness.
Achieving good treatment group assignment is essential for the valid interpretation of study results, as it upholds the integrity of the experimental process.

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Most popular questions from this chapter

Attitudes toward homeless people. Negative attitudes toward poor people are common. Are attitudes more negative when a person is homeless? To find out, a description of a poor person is read to subjects. There are two versions of this description. One begins Jim is a 30-year-old single man. He is currently living in a small single-room apartment. The other description begins lim is \(a\) 30-year-old single man. He is currently homeless and fives in a shelter for homeless people. Otherwise, the descriptions are the same. After reading the description, you ask subjects what they believe about Jim and what they think should be done to help him. The subjects are 544 adults interviewed by telephone. \({ }^{26}\) Outline the design of this experiment.

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Does peer victimization during adolescence have an impact on depression in early adulthood? A recent study in the United Kingdom examined data on 3898 participants for which they had information on both victimization by peers at age 13 and the presence of depression at age 18 . The study found more than a twofold increase in the odds of depression between children who were not victimized and those who were frequently victimized." 20 This is an example of (a) an observational study. (b) a randomized comparative experiment. (c) a matched pairs experiment.

The Community Intervention Trial for Smoking Cessation asked whether a communitywide advertising campaign would reduce smoking. The researchers located 11 pairs of communities, with each pair similar in location, size, economic status, and so on. One community in each pair was chosen at random to participate in the advertising campaign and the other was not. This is (a) an observational study. (b) a matched pairs experiment. (c) a completely randomized experiment.
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