Seminar #21Karen Jakubowski
Finding 95% Confidence Intervals: An approximate 95% confidence interval for
unknown population proportion p is based on sample proportion p-hat from a random sample of size n
= sample proportion +/- 2 standard deviations
Article #1: The White Coat Syndrome
Some people exhibit a psychophysiological response to seeing doctors or other medical professionals
This has been termed the “White Coat Syndrome” or “White Coat Hypertension” Patients suffer from hypertension only when in the
presence of a person in a “white coat.”
Study design: Study involved 419 patients who exhibited
hypertension while at their doctor’s office. They were provided with portable blood pressure-
measuring devices that measured their levels outside of the office.
Results: 26% (109) of the patients suffered from
hypertension only while visiting their physician.
What are some possible reasons that individuals exhibit the “White Coat Syndrome?” Fear of bad news Knowledge of experiences of friends/family Embarrassment (ie: have not been taking
medication regularly or following past directions)
Finding 95% Confidence Interval .26 +/- 2SqRoot (.26(1-.26)) / (419)
= (.217, .303)
Article #2: Nine Percent of U.S. Children Age 8 to 15 Meet Criteria For Having ADHD 8.7% of U.S. children age 8 to 15 meet
diagnostic criteria for ADHD fewer than half receive treatment
ADHD is characterized by hyperactivity, impulsive behavior, and an inability to pay attention to tasks.
Study Design: Study involved 3,082 children
sample population designed to represent the entire population of 8 to 15-year-olds in the U.S.
Parents/caregivers provided information about their child’s ADHD symptoms and medical history, as well as sociodemographic details via phone interview.
Study Design: How could this study design have been
flawed? Some parents may not have been entirely
truthful about their child’s ADHD symptoms or medical history.
Bias from parents’ inaccurate memories about when their child first displayed symptoms of ADHD or the severity of the symptoms.
Finding 95% Confidence Interval 8.7% (268) of the 3,082 children studied
fulfilled criteria for ADHD. .087 +/- 2SqRt ((.087(1-.087)) / 3082
= (.077, .097)
Finding 95% Confidence Interval 47.9% of the children who met ADHD
criteria (268 children) had been previously diagnosed with the condition.
Before we calculate the interval, do you think that the children meeting ADHD criteria who had been diagnosed were in a minority?
Finding 95% Confidence Interval .479 +/- 2SqRt ( (.479 (1-.479)) / 268 )
= (0.42, 0.54)
Since the values in our interval surround .5 , we cannot be certain that the children who were diagnosed with ADHD were in a minority.
Article #3: Surgeons With Video Game Skill Appear To Perform Better In Simulated Surgery Skills Course Study involved 33 surgeons: 12 attending
physicians and 21 residents Asked about their video game-playing habits, then
assessed on their performance at the Rosser Top Gun Laparoscopic Skills and Suturing Program A 1.5 day course that scores surgeons on time and errors
during simulated surgery skills.
Results: Surgeons who had played video games in the past
for more than 3 hours/week made 37% fewer errors, were 27% faster, and scored 42% better overall than surgeons who never played video games.
Current video game players made 32% fewer errors, were 24% faster and scored 26% better overall than non-players.
Surgeons in the top 1/3 of gaming skill made 47% fewer errors, performed 39% faster, and scored 41% better overall than those in the bottom 1/3.
Does anyone notice a problem …?
From the information provided, we cannot find 95% confidence intervals! The data was summarized in quantitative terms, but we
were not given any mean values, just percentages comparing how much higher the mean for one group is compared to another.
Therefore we cannot set up a confidence interval around a proportion in this example.
Article #4: U.S. College Students’ Exposure to Tobacco Promotions: Prevalence and Association With Tobacco Use This study assessed college students’
exposure to the tobacco industry marketing strategy of sponsoring social events at bars, nightclubs, and college campuses.
Study design: Data came from the 2001 Harvard College
Alcohol Study - a random sample of 10,904 students enrolled in
119 “nationally representative” 4-year colleges and universities.
Study design: Questionnaires were mailed to 21,055 students in
February 2001. 3 mailings were sent within 3 weeks: the
questionnaire, a reminder, and a second questionnaire.
Responses were anonymous, and cash prizes were awarded to encourage responses.
What types of questions should the questionnaire have included?
Study design: The questionnaire assessed students’:
demographics (ie: age, sex, race, GPA) tobacco, alcohol, and marijuana use
Tobacco use was defined as having (in the past 30 days): smoked a cigarette, cigar, pipe, or bidi (a small
hand-rolled often flavored cigarette made in India)
used smokeless tobacco
Study design: What aspects of this study reduced bias?
Using a large sample Using a sample that was representative of the
larger college student population Anonymous questionnaire
Study design: What aspects of this study could have
caused bias? Non-response bias Not answering the questions truthfully Wording of the questions
Results: 52% (5,670 students) responded to the
questionnaire
Do you think that 52% a good response rate? Does it provide enough information to allow
accurate inferences to be made about the larger population of college students?
Results: The effect of exposure of tobacco promotions
differed by the age at which students first began smoking
Out of the 78% (8482) of students who did not smoke regularly before 19 years of age (approximately the age most students enter college) the current smoking rate was 23.7% for students who had attended a promotional event 11.8% for students who had not attended an event
Finding 95% Confidence Interval For the 23.7% of students who had not smoked before
age 19, but were current smokers and had attended a promotional event:.237 +/- 2SqRt ( (.237(1-.237)) / 8482)
= (.227, .246)
For the 11.8% of students who had not smoked before age 19, but were current smokers and had never attended a promotional event:.118 +/- 2SqRt (.118(1-.118)) / 8482
= (.111, .125)
What does it mean? Since the confidence intervals for the two
separate groups do not overlap, the data suggests that one population proportion is higher than the other.
Results: For the 22% (2334) of students who
smoked regularly before 19 years of age, there was no significant difference between the percentage of students who had or had not attended a tobacco promotional event. 77.5% vs 72.2%, respectively
Conclusion: Tobacco promotional events may
encourage previously non-smoking college students to begin smoking, or current smokers to continue smoking.
The End!