Biometry ~ Types of Studies

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Research classifications • Observational vs. Experimental

Observational

– researcher collects info on attributes or measurements of interest, but

does not

influence results.

Experimental

– researcher deliberately influences events and investigates the effects of the intervention, e.g. clinical trials and laboratory experiments.

We often use these when we are interested in studying the effect of a treatment on individuals or experimental units.

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Experiments & Observational Studies We conduct an

experiment

when it is (ethically, physically etc) possible for the experimenter to determine which experimental units receive which treatment.

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Experiments & Observational Studies

Experiment Terminology Experimental Unit Treatment Response

patient worm tomatoes mouse drug drug fertilizer radiation cholesterol protein level yield mortality C1, L3-4, S4

Experiments & Observational Studies In an observational study , we compare the units that happen to have received each of the treatments.

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Experiments & Observational Studies

Unit

patient potatoes walleye

Observational Study Treatment

smoking

Response

lung cancer weather waterway yield Hg level e.g. You cannot set up a control (non-smoking) group and treatment (smoking) group.

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Experiments & Observational Studies

Note:

Only a well-designed and well-executed experiment causation.

can reliably establish An observational study is useful for identifying possible causes of effects, but it cannot reliably establish causation .

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1. Completely Randomized Design The treatments are allocated entirely by chance to the experimental units.

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1. Completely Randomized Design Example: Which of two varieties of tomatoes (A & B) yield a greater quantity of market quality fruit?

Factors that may affect yield: • different soil fertility levels • exposure to wind/sun • soil pH levels • soil water content etc.

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1. Completely Randomized Design Divide the field into plots and randomly allocate the tomato varieties (treatments) to each plot (unit).

8 plots – 4 get variety A

UPHILL 1 5 (A) (B) 2 6 (A) 3 7 (A) (B) 8 (B) (B) Randomly assign A & B varieties in each strip of What if the field sloped upward from left to right?

Discuss for ½ Minute C1, L3-4, S10

1. Completely Randomized Design

Note:

Randomization is an attempt to make the treatment groups as similar as possible — we can only expect to achieve this when there is a large number of plots.

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2. Blocking Group (block) experimental units by some known factor and then randomize within each block in an attempt to balance out the unknown factors.

Use:

• blocking for known factors

(e.g. slope of field in previous example) and

• randomization for unknown

factors to try to “balance things out”.

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2. Blocking Example continued: It is recognized that there are two areas in the field – well drained and poorly drained.

Partition the field into two blocks and then randomly allocate the tomato varieties to plots within each block.

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2. Blocking Well drained Poorly drained

1 (A) 2 (B) 3 (A) 4 (B) 1 (B) 3 (A) 2 (A) 4 (B) 5 (A) 6 (A)

7 (B)

8 (B)

How should we allocate varieties to plots?

Discuss in groups for 1/2 minute.

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2. Blocking Example 2: Comparing Three Pain Relievers for Headache Sufferers • How could blocking be used to increase precision of a designed experiment to control to compare the pain relievers?

• What are some other design issues?

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Example 3: Comparing 17 Different Leg Wraps on Used on Race Horses • 17 “boots” tested, each boot is tested

n = 5

times. Why?

• Because of the time constraints all boots were not tested on the same day.

• 8 tested 1 st 3 rd day.

day, 5 tested 2 nd day, 4 tested • Leg was placed in freezer and thawed before the 2 nd and 3 rd days of testing.

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Horse Leg Wraps (cont’d) • What problems do you foresee with this experimental design?

Discuss

• What actually happened?

Forces readings obtained from cadaver leg when no boot or wrap was used.

What are the implications of these results?

Discuss

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Horse Leg Wraps (cont’d)

FINAL BOOT COMPARISONS

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Horse Legs Wraps (cont’d) • What should have been done?

Discuss

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3. People as Experimental Units

Example: Cholesterol Drug Study –

Suppose we wish to determine whether a drug will help lower the cholesterol level of patients who take it. How should we design our study?

Discuss for two minutes in groups.

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Polio Vaccine Example C1, L3-4, S21

Polio Vaccine Example Iron Lung Dr. Jonas Salk, vaccine pioneer 1914-95 C1, L3-4, S22

The Salk Vaccine Field Trial • 1954 Public Health Service organized an experiment to test the effectiveness of Salk’s vaccine.

• Need for experiment: – Polio, an epidemic disease with cases varying considerably from year to year. A drop in polio after vaccination could mean either: • Vaccine effective • No epidemic that year C1, L3-4, S23

The Salk Vaccine Field Trial Subjects: 2 million, Grades 1, 2, and 3 • 500,000 were vaccinated – (Treatment Group) • 1 million deliberately not vaccinated – (Control Group) • 500,000 not vaccinated - parental permission denied C1, L3-4, S24

The Salk Vaccine Field Trial

NFIP Design

• Treatment Group: Grade 2 • Control Group: Grades 1 and 3 + No Permission

Flaws ?

Discuss for 30 seconds.

• Polio contagious, spreading through contact. i.e. incidence could be greater in Grade 2 (bias against vaccine), or vice-versa.

• Control group included children without parental permission (usually children from lower income families) whereas Treatment group could not (bias against the vaccine).

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The Salk Vaccine Field Trial Double-Blinded Randomized Controlled Experimental Design • Control group only chosen from those with parental permission for vaccination • Random assignment to treatment or control group • Use of placebo (control group given injection of salted water) • Diagnosticians not told which group the subject came from (polio can be difficult to diagnose) • i.e., a double-blind randomized controlled experiment C1, L3-4, S26

The Salk Vaccine Field Trial The double-blind randomized controlled experiment (and NFIP) results (NFIP rate) Treatment Control Size of group 200,000 200,000 No consent 350,000 Rate per 100,000 28 71 46 (25) Grade 2 (54) Grade 1/3 (44) Grade 2 C1, L3-4, S27

3. People as Experimental Units • control group: – Receive no treatment or an existing

treatment

• blinding: – Subjects don’t know which treatment

they receive

• double blind: – Subjects and administers /

diagnosticians are blinded

• placebo: – Inert dummy treatment C1, L3-4, S28

3. People as Experimental Units • placebo effect: – A common response in humans when they

believe they have been treated.

– Approximately 35% of people respond

positively to dummy treatments - the placebo effect

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Observational Studies • There are two major types of observational studies: prospective and retrospective studies C1, L3-4, S30

Observational Studies 1. Prospective Studies – (looking forward) – Choose samples now, measure variables and follow up in the future.

– E.g., choose a group of smokers and non-smokers now and observe their health in the future.

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Observational Studies 2. Retrospective Studies – (looking back) – Looks back at the past.

– E.g., a case-control study • Separate samples for cases and controls (non-cases). • Look back into the past and compare histories. • E.g. choose two groups: lung cancer patients and non-lung cancer patients. Compare their smoking histories.

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Observational Studies

Important Note:

1. Observational studies should use some form of random sampling to obtain representative samples.

2. Observational studies cannot reliably establish causation.

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Controlling for various factors • A prospective study was carried out over 11 years on a group of smokers and non smokers showed that there were 7 lung cancer deaths per 100,000 in the non smoker sample, but 166 lung cancer deaths per 100,000 in the smoker sample.

• This still does not show smoking causes lung cancer because it could be that smokers smoke because of stress and that this stress causes lung cancer. C1, L3-4, S34

Controlling for various factors • To control for this factor we might divide our samples into different stress categories. We then compare smokers and non-smokers who are in the same stress category.

• This is called

controlling

confounding factor

.

for a C1, L3-4, S35

Example 1 • “Home births give babies a good chance” NZ Herald, 1990 – An Australian report was stated to have said that babies are twice as likely to die during or soon after a hospital delivery than those from a home birth.

– The report was based upon simple random samples of home births and hospital births.

Q: Does this mean hospitals are dangerous places to have babies in Australia? Why or why not?

Discuss for 1 minute in groups.

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Example 2 • “Lead Exposure Linked to Bad Teeth in Children” ~ USA Today The study involved 24,901 children ages 2 and older. It showed that the greater the child’s exposure to lead, the more decayed or missing teeth.

Q: Does this show lead exposure causes tooth decay in children? Why or why not?

Discuss for 1 minute.

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Example 2 ~ cont’d • “Lead Exposure Linked to Bad Teeth in Children” ~ USA Today Researcher: “We

controlled

for income level, the proportion of diet due to carbohydrates, calcium in the diet and the number of days since the last dental visit.” C1, L3-4, S38

Additional Example 1 – Determine Whether Age at 1

st

Pregnancy is a Risk Factor for Cervical Cancer

How might we proceed?

Discuss

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Additional Example 2 – Determine what factors might influence the “success” of a duck nest.

How might we proceed?

Discuss

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Additional Example 3 – Test the toxicity of a new pesticide/herbicide on aquatic organisms.

How might we proceed?

Discuss

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