DAY 4 Considerations for Interpretation Bias Participation Rate Reversed Time Order

DAY 4

Considerations for Interpretation

Bias

Participation Rate

Reversed Time Order

1

EPI CHALLENGEProposal Form

7. Considerations for InterpretationParticipation Rate

7b. Describe what the term “participation rate” means, and explain why it is important to know it. Use a formula or diagram if you wish.

Explain how you will calculate the participation rate for your study.

EPI Challenge

Master Proposal Form

Name of Team Member

________________

EPI CHALLENGEProposal Form

7. Considerations for InterpretationRepresentativeness

7c. Describe why representativeness is important in the interpretation of your study results.

Develop an additional question for your survey that will help your team determine the representativeness of the group of students that participated in your study.

EPI Challenge

Master Proposal Form

Name of Team Member

________________

EPI CHALLENGEProposal Form

7. Considerations for InterpretationBias and Reversed Time Order

7d. Describe one form of bias that might influence the possible association between your exposure and outcome.

7e. Describe how reversed time order might affect your interpretation of study results.

EPI Challenge

Master Proposal Form

Name of Team Member

________________

6

One possible explanation for finding an association is because the exposure causes the outcome.

Because observational studies are complicated by factors not controlled by the investigator,

other explanations also must be considered, including, confounding,

bias, and reversed time order.

Big Epi Idea

7

One possible explanation for finding an association is because the exposure causes the outcome.

Because observational studies are complicated by factors not controlled by the investigator,

other explanations also must be considered, including, confounding,

bias, and reversed time order.

Big Epi Idea

8

Bias

9

Any systematic error in the design, conduct, or analysis of a study that results in a mistaken estimate of an exposure’s effect on the outcome

Bias

10

Any systematic error in the design, conduct, or analysis of a study that results in a mistaken estimate of an exposure’s effect on the outcome

Bias

In a x-sectional study,

what do we call the

estimate of an

exposure’s effect on

the outcome?

11

9010

9010

b

d

a

c

Total

Exposure

No Exposure

OutcomeNo

Outcome

Any systematic error in the design, conduct, or analysis of a study that results in a mistaken estimate of an exposure’s effect on the outcome

Outcome Prevalences

Prevalence Ratio

BiasIn a x-sectional study,

what do we call the

estimate of an

exposure’s effect on

the outcome?

60%

20%

12

9010

9010

b

d

a

c

Total

Exposure

No Exposure

OutcomeNo

Outcome

1

Any systematic error in the design, conduct, or analysis of a study that results in a mistaken estimate of an exposure’s

effect on the outcome

Outcome Prevalences

Prevalence Ratio

Bias

50%

50%

13

9010

9010

b

d

a

c

Total

Exposure

No Exposure

OutcomeNo

Outcome

.5

Any systematic errorin the design, conduct, or analysis of a study that results in a mistaken estimate of an exposure’s effect on the outcome

Outcome Prevalences

Prevalence Ratio

Bias

25%

50%

14

9010

9010

b

d

a

c

Total

Exposure

No Exposure

OutcomeNo

Outcome

2

Outcome Prevalences

Prevalence Ratio

Bias

50%

25%

Any systematic errorin the design, conduct, or analysis of a study that results in a mistaken estimate of an exposure’s effect on the outcome

15

16

A flaw in measuring exposure or outcome data that results in different quality of data between comparison groups

Information Bias

17

A flaw in measuring exposure or outcome data that results in different quality of data between comparison groups

Information Bias

18

9010

9010

b

d

a

c

Total

Alcohol

No Alcohol

Birth Defect

1

A flaw in measuring exposure or outcome data that results in different quality of data between

comparison groups

Outcome Prevalences

Prevalence Ratio

Information Bias

No Birth

Defect

5%

5%

19

9010

9010

b

d

a

c

Total

Alcohol

No Alcohol

Birth Defect

1

A flaw in measuring exposure or outcome data that results in different quality of data between

comparison groups

Outcome Prevalences

Prevalence Ratio

Information Bias

No Birth

Defect

5%

5%

20

9010

9010

b

d

a

c

Total

Sports Participation

No Sports

Participation

High GPA

3

Outcome Prevalences

Prevalence Ratio

Information Bias

Low GPA

60%

20%

A flaw in measuring exposure or outcome data that results in different quality of data between

comparison groups

21

9010

9010

b

d

a

c

Total

Hyper Texting

No Hyper

Texting

Low GPA

1

Outcome Prevalences

Prevalence Ratio

Information Bias

High GPA

30%

30%

A flaw in measuring exposure or outcome data that results in different quality of data between

comparison groups

22

A flaw in measuring exposure or outcome data that results in different quality of data between comparison groups

Information Bias

Systematic error due to differences in the accuracy and completeness of the recall to memory of past experiences

Recall Bias

23

A flaw in measuring exposure or outcome data that results in different quality of data between comparison groups

Information Bias

Systematic error due to differences in the accuracy and completeness of the recall to memory of past experiences

Recall Bias

24

Recall Bias

25

9010

9010

b

d

a

c

Total

Exposure

No Exposure

OutcomeNo

Outcome

1

Systematic error due to differences in the accuracy and completeness of the recall to memory of past experiences

Outcome Prevalences

Prevalence Ratio

Recall Bias

30%

30%

26

9010

9010

b

d

a

c

Total

Stress

No Stress

4

Outcome Prevalences

Prevalence Ratio

Recall Bias

Birth Defect

No Birth

Defect

8%

2%

Systematic error due to differences in the accuracy and completeness of the recall to memory of past experiences

27

28

Error due to systematic differences in characteristics between those who take part in a study and those who do not

Selection Bias

29

9010

9010

b

d

a

c

Total

Exposure

No Exposure

OutcomeNo

Outcome

1

Error due to systematic differences in characteristics between those who take part in a study and those who do not

Outcome Prevalences

Prevalence Ratio

Selection BiasDid Not

Participate

Did Participate

25%

25%

30

9010

9010

b

d

a

c

Total

Marijuana

No Marijuana

Low GPA

1

Outcome Prevalences

Prevalence Ratio

High GPA

Error due to systematic differences in characteristics between those who take part in a study and those who do not

Selection BiasDid Not

Participate

Did Participate

25%

25%

31

9010

9010

b

d

a

c

Total

More Sleep

Less Sleep

More Physical Activity

4.7

Outcome Prevalences

Prevalence Ratio

Less Physical Activity

Did Not Participate

Did Participate

Error due to systematic differences in characteristics between those who take part in a study and those who do not

Selection Bias

66.7%

14.3%

32

One possible explanation for finding an association is because the exposure causes the outcome.

Because observational studies are complicated by factors not controlled by the investigator,

other explanations also must be considered, including, confounding,

bias, and reverse time order.

Big Epi Idea

33

Non-response is a particular problem affecting cross-sectional studies and can result in bias of the measures of outcome.

From Epi Textbooks

35

The number of completed survey instruments divided by the total number of persons who would have been surveyed if all participated.

Usually expressed as a percentage.

Participation Rate

36

Results

The completed interview rate for adolescents was 48%.

Participation Rate

37

Results

The completed interview rate for adolescents was 48%.

What do you want your response rate to be?

Participation Rate

What did the

investigators

need to do

in order to

calculate their

participation rate?

38

The completed interview rate for adolescents was 48%.

Results

XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

Xxxxxx, Xxxxxx, Xxxxxx, Xxxxxx, Xxxxxx

EPIC Summer Session 2 Presentations

June 26, 2015

XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

What will you

need to do

in order to

calculate your

participation rate?

Calculate Your Participation Rate

39

40

A representative sample resembles the population from which it was taken in some way.

Representative Sample

Non-response is a particular problem affecting cross-sectional studies and can result in bias of the measures of outcome.

From Epi Textbooks

Non-response is a particular problem affecting cross-sectional studies and can result in bias of the measures of outcome. This is a particular problem when the characteristics of non-responders differ from responders.

From Epi Textbooks

43

Representativeness of Participants

Are the 48% who participated similar or dissimilar to those who were invited to participate?

Results

The completed interview rate for adolescents was 48%.

What could the

investigators

have done to get

a sense of the

representativeness

of the participants

in their

investigation?

44

Results

The grade levels of the adolescents invited to participate were 25% freshmen, 25% sophomores, 25% juniors, and 25% seniors.

Representativeness of Participants

The grade levels of the adolescents who did participate were 25% freshmen, 25% sophomores, 25% juniors, and 25% seniors.

Are the 48% who participated similar or dissimilar to those who were invited to participate?

45

Results

The grade levels of the adolescents invited to participate were 25% freshmen, 25% sophomores, 25% juniors, and 25% seniors.

Representativeness of Participants

The grade levels of the adolescents who did participate were 40% freshmen, 30% sophomores, 20% juniors, and 10% seniors.

Are the 48% who participated similar or dissimilar to those who were invited to participate?

46

Results

The distribution of the schools among possible SS1 survey participants was 20% Cedar Cliff, 20% John Harris, 20% Lower Dauphin, 20% Middletown Area, and 20% Sci Tech

.

EPIC Summer Session 1 Survey

Wednesday, June 23, 2014

The answer to

what question

from our SS1

survey could be

used to get a

sense of the

representativeness

of the SS1

participants who

completed the

survey?

Representativeness of Participants

Are the XX% who participated similar or dissimilar to those who were invited to participate?

The distribution of the schools among the actual SS1 survey participants was 20% Cedar Cliff, 20% John Harris, 20% Lower Dauphin, 20% Middletown Area, and 20% Sci Tech

.

47

Results

The distribution of the schools among possible SS1 survey participants was 20% Cedar Cliff, 20% John Harris, 20% Lower Dauphin, 20% Middletown Area, and 20% Sci Tech

.

EPIC Summer Session 1 Survey

Monday, June 23, 2014

Representativeness of Participants

Are the XX% who participated similar or dissimilar to those who were invited to participate?

The distribution of the schools among the actual SS1 survey participants was ___% Cedar Cliff, ___% John Harris, ___% Lower Dauphin, ___% Middletown Area, and ___% Sci Tech

.

48

The completed interview rate for adolescents was 48%.

Results

XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

Xxxxxx, Xxxxxx, Xxxxxx, Xxxxxx, Xxxxxx

EPIC Summer Session 2 Presentations

June 26, 2015

XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

What question

can you include

in your survey

so that you can get

a sense of the

representativeness

of your participants?

Representativeness of Participants

49

50

One possible explanation for finding an association is because the exposure causes the outcome.

Because observational studies are complicated by factors not controlled by the investigator,

other explanations also must be considered, including confounding,

bias, and reversed time order.

From Epi Textbooks

Egg Chicken

51

Which happened first?

52

A cross-sectional study is a study in which exposure and outcome are measured simultaneously in a given population or a sample of that population. This study can be thought of as providing a "snapshot" of the frequency of an exposure and outcome at a particular point in time. Data that are collected as part of a cross-sectional study can be used to assess the prevalence of an outcome. Also called a prevalence study.

Cross-Sectional Study

Cross-sectional studies are carried out to investigate possible associations between hypothesized exposures and outcomes.

From Epi Textbooks

Cross-sectional studies are carried out to investigate possible associations between hypothesized exposures and outcomes. They are limited, however, by the fact that they are carried out at one time point and give no indication of the sequence of events — whether exposure occurred before, after or during the onset of the outcome.

From Epi Textbooks

Cross-sectional studies are carried out to investigate possible associations between hypothesized exposures and outcomes. They are limited, however, by the fact that they are carried out at one time point and give no indication of the sequence of events — whether exposure occurred before, after or during the onset of the outcome. This being so, it is impossible to infer causality.

From Epi Textbooks

Cross-sectional studies are carried out to investigate possible associations between hypothesized exposures and outcomes. They are limited, however, by the fact that they are carried out at one time point and give no indication of the sequence of events — whether exposure occurred before, after or during the onset of the outcome. This being so, it is impossible to infer causality. Nevertheless, cross-sectional studies can indicate associations that may exist and therefore are supportive of continuing to investigate hypotheses with other study designs.

From Epi Textbooks

57

4 Basic Epidemiological Study Designs

58

A situation in which the hypothesized time order of an exposure and an outcome is actually reversed and the “outcome” actually comes before the “exposure.”

Reversed Time Order

59

Family MealsGood

Mental Health

Family Meals Associated with Good Mental Health

X-Sectional Study

60

Obesity Watching TV

Obesity Linked to Watching TV

X-Sectional Study

61

9010

9010

b

d

a

c

or

or

Total

More Sleep

Less Sleep

More Physical Activity

5

Outcome Prevalences

Prevalence Ratio

50 50

10 90

100

100

100

100

50

10

Less Physical Activity

50%

10%

More Sleep Associated with More Physical Activity

62

More Sleep

More Physical Activity

More Sleep Associated with More Physical Activity

X-Sectional Study

63

Spanking Aggression

Spanking and Aggression

X-Sectional Study

64

Violent Video Games Can Increase Aggression

65

Violent Video Games

Aggression

Violent Video Games Can Increase Aggression

Playing violent

video games

often may well

cause increases

in aggressive

behavior.

X-Sectional Study

66

... the study of the distribution and determinants of health-related states or events in specified populations and the application of this study to the control of health problems.

Epidemiology

67

Violent Video Games

Aggression

Violent Video Games Can Increase Aggression

Playing violent

video games

often may well

cause increases

in aggressive

behavior.

It could be that … highly aggressive individuals are especially attracted to violent video games.

“… the control of health problems.”

X

X-Sectional Study

68

Violent Video Games

Aggression

Violent Video Games Can Increase Aggression

Playing violent

video games

often may well

cause increases

in aggressive

behavior.

It could be that … highly aggressive individuals are especially attracted to violent video games.

X

“… the control of health problems.”

X-Sectional Study

69

A cross-sectional study is a study in which exposure and outcome are measured simultaneously in a given population or a sample of that population. This study can be thought of as providing a "snapshot" of the frequency of an exposure and outcome at a particular point in time. Data that are collected as part of a cross-sectional study can be used to assess the prevalence of an outcome. Also called a prevalence study.

Cross-Sectional Study

71

One possible explanation for finding an association is because the exposure causes the outcome.

Because observational studies are complicated by factors not controlled by the investigator,

other explanations also must be considered, including confounding,

bias, and reversed time order.

From Epi Textbooks

72

A cross-sectional study is a study in which exposure and outcome are measured simultaneously in a given population or a sample of that population. This study can be thought of as providing a "snapshot" of the frequency of an exposure and outcome at a particular point in time. Data that are collected as part of a cross-sectional study can be used to assess the prevalence of an outcome. Also called a prevalence study.

Cross-Sectional Study

73

Cross-Sectional Study

• Difficult to determine whether the outcome followed exposure in time or exposure resulted from the outcome.

• Not suitable for studying rare outcomes or outcomes with a short duration.• As cross-sectional studies measure prevalent rather than incident cases,

the data will always reflect determinants of survival as well as etiology.• Susceptible to bias due to low response and misclassification due to recall

bias.

Limitations

74

Cross-Sectional Study

• Relatively quick and easy to conduct (no long periods of follow-up)• Data on all variables are only collected once• Able to measure prevalence for all factors under investigation• Multiple outcomes and exposures can be studied

Strengths

75

"There must be something in the coffee."

4 New Mothers with 6 Babies in Strollers

Which happened first?

77

Which happened first?