Bio Final Review.pdf - Supplementary material might be...

AS745 Biostatistics and
Research Design
Final Review Session
School of Pharmacy - June 2022
Pantelina Zourna-Hargaden MD, PhD, MPH
Associate Professor

Types of Samples
2
Data may be generated by:
I. Naturalistic Samples. An SRS with data then cross-
classified according to the explanatory variable and
response variable.
II. Purposive Cohort Samples. Fixed numbers of
individuals selected according to the explanatory
factor.
III. Case-Control Samples. Fixed numbers of
individuals selected according to the outcome variable.

Illustrative Example
3
Take an SRS from the population; then cross-classify
individuals with respect to explanatory and response
variables.

Purposive Cohort Samples: Illustrative
Example
4
Select predetermined numbers of exposed and nonexposed
individuals; then ascertain outcomes in individuals.
c Writing Group for the Women’s Health Initiative Investigators. (2002). Risks and benefits
of estrogen plus progestin in healthy postmenopausal women: Principal results from the
Women’s Health Initiative randomized controlled trial. JAMA, 288 (3), 321 – 333.

5
Case-Control Samples: Illustrative Examples
Identify individuals who are positive for the outcome (cases);
then sample the population for negative (controls).

Naturalistic and Cohort Samples
6
◼
Data from a
naturalistic sample are
shown in this 5-by-2
table
◼
Let us always put
the explanatory
variable in row of
such table (for
uniformity)
◼
Totals are tallied in
table margins

Randomized trials patients
7
Patients in randomized trials are not a random sample from
the population of people with the disease in question but are
a highly selected set of patients who were available and were
willing to participate.
However, it is possible to randomize this set into treated and
untreated groups so that any differences in outcomes between
the two treatment groups are due solely to differences in the
treatment to be studied.

Randomized trials
8
Supposing that a well-designed randomized controlled trial in
children with a particular disease found that 20 per cent of the
control group developed bad outcomes, compared with only 12 per
cent of those receiving treatment.
Should you agree to give this treatment to your child? Without
knowing more about the adverse effects of the therapy, it appears to
reduce some of the bad outcomes of the disease.
But is its effect meaningful?

Randomized trials
9
Consider the risk of treatment versus no treatment.
In healthcare, risk refers to the probability of a bad outcome in
people with the disease.
Absolute risk reduction (ARR) – also called risk difference (RD) – is
the most useful way of presenting research results to help your
decision-making.
In this example, the ARR is 8 per cent (20 per cent - 12 per cent = 8
per cent).

Randomized trials
10
Consider the risk of treatment versus no treatment.