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7. Samples and observational studies
The Practice of Statistics in the Life Sciences Third Edition © 2014 W.H. Freeman and Company
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Objectives (PSLS Chapter 7)
Samples and observational studies Observation versus experiment Population versus sample The role of randomness in sampling The simple random sample (SRS) Other probability samples Sample surveys Comparative observational studies
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Observational versus experimental studies
Observational study: record data on individuals without attempting to influence the responses. In 1992, several major medical organizations said that women should take hormones such as estrogen after menopause, because women who took hormones seemed to reduce their risk of a heart attack by 35% to 50%. Experimental study: Deliberately impose a treatment on individuals and record their responses. Influential factors can be controlled. The first statement describes the results of observational studies. Access to medical care, lifestyle, socioeconomic status, are possible confounding variables. The second statement describes experiments, with a random assignment of subjects to treatment. By 2002, several studies concluded that hormone replacement does not reduce the risk of heart attacks. These studies had assigned women to either hormone replacement or to dummy pills. The assignment was done by a coin toss.
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Randomized experiment. Neither. This is just anecdotal evidence.
A 2013 Gallup study investigated how phrasing affects the opinions of Americans regarding physician-assisted suicide. Telephone interviews were conducted with a random sample of 1,535 national adults. Using random assignment, 719 heard the question in Form A and 816 the one in Form B. Form A: When a person has a disease that cannot be cured, do you think doctors should be allowed by law to end the patient’s life by some painless means if the patient and his or her family request it? Form B: When a person has a disease that cannot be cured and is living in severe pain, do you think doctors should or should not be allowed by law to assist the patient to commit suicide if the patient requests it? The individuals surveyed did not choose which question they heard. This was done by Gallup, using random assignment. Therefore this is a comparative randomized experiment. 70% of those given Form A answered “should be allowed”, compared with only 51% of those given Form B. What type of study is this? Observational study. Randomized experiment. Neither. This is just anecdotal evidence.
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Confounding Two variables are confounded when their effects on a response variable cannot be distinguished. Observational studies often fail to yield clear causal conclusions, because the explanatory variable is confounded with lurking variables. Observational studies play an important role in the building of scientific knowledge, but they cannot establish whether observed differences between groups can be attributed to the groups’ differentiating feature or to confounding variables. Experiments, on the other hand, provide an opportunity for manipulating the environment and confounding variables. Therefore, well-designed experiments yield stronger conclusions. CONFOUNDING?
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This is an observational study
This is an observational study. When explaining greater autism diagnoses, higher education and higher access to health care are confounded.
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Population versus sample
Population: The entire group of individuals in which we are interested but can’t usually assess directly A parameter is a number summarizing a characteristic of the population. Sample: The part of the population we actually examine and for which we do have data A statistic is a number summarizing a characteristic of a sample. Population Sample How well the sample represents the population depends on the sample design. Parameters are often referred to by a Greek letter, whereas statistics are typically labeled using English letters (sometimes in combination with math symbols).
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The role of randomness in sampling
How do you select the individuals/units in a sample? Voluntary response sampling: individuals choose to be involved Convenience sampling: ask whoever is around (mall, street) or take the next 10 units Probability sampling: individuals or units are randomly selected; the sampling process is unbiased Voluntary response samples and convenience samples are not scientific because they are not truly representative of the whole population of interest; rather, they tend to be strongly biased.
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But a random sample showed that 91% of parents WOULD have kids again.
Ann Landers summarizing responses of readers: 70% of (~10,000) parents wrote in to say that having kids was not worth it—if they had to do it over again, they wouldn’t. But a random sample showed that 91% of parents WOULD have kids again. What do you think explains such drastically different responses? Would you expect very different responses on the potential legalizing of marijuana if you asked the first people you saw on the parking lot of a university or the first people you saw on the parking lot of a church? Most letters to newspapers are written by disgruntled people. They are not representative of the population of interest (all parents). People you find in one location may be very different from the people you would find at a different location. Restricting your sample to one location for convenience means that your sample will not be representative of your whole population of interest (here, probably the adult population). Visit for other examples of bad sampling.
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The simple random sample
A Simple Random Sample (SRS) is made of randomly selected individuals. Each individual in the population has the same probability of being in the sample. All possible samples of size n have the same chance of being drawn. How to choose an SRS? Draw from a hat (lottery style) Flip a coin Use a table of published random numbers (Table A) Use software that generates random numbers
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Choosing a simple random sample with Table A
We need to select a random sample of 5 from a class of 20 students. List and number all members of the population, which is the class of 20. The number 20 is two digits long. Parse the list of random digits into numbers that are two digits long. Here we chose to start with line 103, for no particular reason.
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… 01 Alison 02 Amy 03 Brigitte 04 Darwin 05 Emily 06 Fernando 07 George 08 Harry 09 Henry 10 John 11 Kate 12 Max 13 Moe 14 Nancy 15 Ned 16 Paul 17 Ramon 18 Rupert 19 Tom 20 Victoria We then move on to line 104. The next three to be selected are Moe, George, and Amy (13, 7, and 02). Choose a random sample of size 5 by reading through the list of two-digit numbers, starting with line 103 and on. The first five random numbers matching numbers assigned to people make the SRS. The first individual selected is Ramon, number 17. Then Henry (09). That’s all we can get from line 103. Remember that 1 is 01, 2 is 02, etc. If you were to hit 17 again before getting five people, don’t sample Ramon twice—you just keep going.
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Other probability samples
A stratified random sample: make sure your sample has x,y,z% of individuals of certain types A multistage sample: select your final sample in stages, by sampling within a sample within a sample America's State of Mind report was based on a probability sample of Medco's de-identified database of members with 24 months of continuous insurance enrollment. Sampling was stratified by age group and sex to match the demographics of the whole customer base. Multistage samples are often used by the government to survey the whole population, because they are more economical. However, statistical analysis for a multistage sample is more complex than for an SRS. The National Youth Tobacco Survey administered in schools uses a sampling procedure to generate a nationally representative sample of students in grades 6–12. Sampling is probabilistic and consists of selecting: 1) Counties as Primary Sampling Units (PSU). 2) Schools within each selected PSU. 3) Classes within each selected school.
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Sample surveys A sample survey is an observational study that relies on a random sample drawn from the entire population. Opinion polls are sample surveys that typically use voter registries or telephone numbers to select their samples. In epidemiology, sample surveys are used to establish the incidence (rate of new cases per year) and the prevalence (rate of all cases at one point in time) of various medical conditions, diseases, and lifestyles. These are typically stratified or multistage samples.
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Some survey challenges
Undercoverage: Parts of the population are systematically left out. Nonresponse: Some people choose not to answer/participate. Wording effects: Biased or leading questions, complicated/ confusing statements can influence survey results. Response bias: Fancy term for lying or forgetting (especially on sensitive/personal issues). Can be exacerbated by survey method (in person vs. by phone or online). Undercoverage: For instance, surveys of households omit homeless individuals. Surveys conducted online tend to include a younger and more urban population. To avoid undercoverage of individuals with a cell phone but no landline phone (>30% of Americans since 2011), most phone-based surveys now control for phone access (landline only, cell only, both) by stratifying their samples. Nonresponse: A growing issue, especially in commercial polls. Wording effects: Questions worded like “Do you agree that it is awful that…” are prompting you to give a particular response. Small changes in wording can have a substantial effect on responses. Response bias: FQuestions about the past or sensitive issues often get biased responses (“How much do you drink?” or “How much do you weigh?”).
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Pew Research Center methodology survey up to ~ 90% in 2012
How bad is nonresponse? The Census Bureau’s American Community Survey (ACS): ~ 2.5% Via mail with reminders. Response is mandatory. University of Chicago’s General Social Survey (GSS): ~ 30% - In person. Pew Research Center methodology survey up to ~ 90% in 2012 Private polling firms such as SurveyUSA: ~ 90% as of 2002 (stopped showing after that) Phone (with interviewer or automated call) or online. Source:
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A 2013 Gallup study investigated how phrasing affects the opinions of Americans regarding physician-assisted suicide. Telephone interviews were conducted with a random sample of 1,535 national adults. Using random assignment, 719 heard the question in Form A and 816 the one in Form B. Form A: When a person has a disease that cannot be cured, do you think doctors should be allowed by law to end the patient’s life by some painless means if the patient and his or her family request it? Form B: When a person has a disease that cannot be cured and is living in severe pain, do you think doctors should or should not be allowed by law to assist the patient to commit suicide if the patient requests it? Because the two questions were randomly assigned, only question wording differed consistently between the two forms. Any issue of response bias, nonresponse, and undercoverage would apply equally to both questions, and therefore could not explain the substantial difference in opinions. Question wording resulted in a substantial difference in opinions: 70% of those given Form A answered “should be allowed”, compared with only 51% of those given Form B.
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Some examples of possible response bias
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Comparative observational studies
Case-control studies start with 2 random samples of individuals with different outcomes, and look for exposure factors in the subjects’ past (“retrospective”). Individuals with the condition are cases, and those without are controls. Good for studying rare conditions. Selecting controls is challenging. Cohort studies enlist individuals of common demographic, and keep track of them over a long period of time (“prospective”). Individuals who later develop a condition are compared with those who don’t. Cohort studies examine the compounded effect of factors over time. Good for studying common conditions. Very expansive.
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Aflatoxicosis epidemics
Aflatoxins are secreted by a fungus found in damaged crops and can cause severe poisoning and death. The Kenya Ministry of Health investigated a 2004 outbreak of aflatoxicosis resulting in over 300 cases of liver failure. A sample of 40 case-patients and 80 healthy controls were asked how they had stored and prepared their maize. The case-patients were randomly selected from a list of individuals admitted to a hospital during the 2004 outbreak for unexplained acute jaundice. Control individuals were selected to be as similar to the case-patients as possible, yet randomly selected. Preliminary data suggested that soil, microclimate, and farming practices might have played a role, but not age or gender. For each case-patient, two individuals from the patient’s village with no history of jaundice symptoms were randomly selected. The study findings indicate that improper corn storage was a principal source of poisoning.
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The Nurses’ Health Study is one of the largest prospective observational studies designed to examine factors that may affect major chronic diseases in women. Since 1976, the study has followed a cohort of over 100,000 registered nurses. Every two years, they receive a follow-up questionnaire about diseases and health-related topics. Response rate: ~ 90% each time. 2007 report on age-related memory loss: About 20,000 women ages 70+ had completed telephone interviews every two years to assess their memory with a set of cognitive tests. One of the findings: the more women walked during their late 50s and 60s, the better their memory score was at age 70 and older. However, we cannot unambiguously conclude that walking has a protective effect against memory loss.
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