L4. case control study design

4. CASE CONTROL STUDY DESIGN
BY: DESSIE ABEBAW
2/22/2020 DESSIE MPH in EPID/BIOS 1

Learning objectives
By the end of this chapter, the students will be able to :
Discuss the traditional and modern views of case-control studies
List the settings in which case-control studies are desirable
Describe the steps of case control study design
Calculate and interpret measure of association in case control study
Describe the information required to calculate sample size in case control
study
Explain the variants of case control study
 Identify the common biases that introduced in case control studies
Explain the advantage, disadvantage and application of case control
study

Case control study design
• The investigator selects the case group and the control group
on the basis of a defined outcome
• It start with the outcome (disease status) and look backward
for the exposure
• We determine what proportion of the cases were exposed and
what proportion were not.
• We also determine what proportion of the controls were
exposed and what proportion were not.
•

Other terms of case control study
• case comparison study
• case compeer study
• case history study
• case referent study and
• retrospective study??????

Case-Control Studies
Cases: Disease
Controls: No disease

Study
population
Cases
(disease)
Controls
(no disease)
factor present
factor absent
factor present
factor absent
present
past
time
Study begins here2/22/2020 DESSIE MPH in EPID/BIOS 6

1. Traditional view of case control study
• Traditionally, epidemiologists viewed case-control studies as an
alternative to cohort studies
• the logic of this approach differs from that of experimental and
cohort study designs
• experimental and cohort studies move from cause to effect, and case-
control studies move from effect to cause
• Thus, many who espouse the traditional view believe that the logic of
a case-control study is backwards

Traditional view of case control study
• They also believe that case-control studies are much more prone to
bias and thus inferior to other designs
• That is why they spelled “TROHOC” study
• However, epidemiologists’ views about the appropriate way to
conceptualize and design this type of study have changed
considerably over the past Three decades
• Consequently, epidemiologists have come to realize that the quality
of a case-control study can be as high as that of a cohort study.

The Modern View of case control study
• Miettinen asserted, the key comparison in a case-control study is the
same as that in a cohort study, which is a comparison between the
exposed and non exposed groups.
• Unlike traditional case control view, Using odd ratio we can associated
the exposure and the outcome .
• However, unlike the cohort and experimental study, we cannot
calculate an incidence rate of a disease
• because we do not know the size of the population from which the
cases were drawn

The Modern View of case control study
Example
• Nested case control study is much more efficient than the cohort
study
• The cases are the same as those that would be included in the cohort
study
• The controls provide a less expensive and faster way of determining
the exposure experience in the population that generated the cases

2. Versatile, Informative, and Efficient Design
Case control study design is well suited for
rare diseases
 long latency.
It is relatively quick to mount and conduct and
 is reasonably inexpensive.
 requires comparatively few study subjects with very little risk to these
subjects.
 allows us to test multiple hypotheses (evaluation of interaction and
assessment of confounding factors)
How it is versatile, informative and efficient design?

3. QUESTIONS FOR AN ASSESSMENT OF CASE-CONTROL STUDIES
The following questions are useful while designing a case-control study
1. Is there a clear definition of the problem under consideration. Is
this study assessing factors inﬂuencing incidence or mortality?
2. Is the definition of cases consistent with the definition of the
problem?. Are we concerned with cerebrovascular accidents as a
problem or the subset of hemorrhagic strokes?
3. Are the controls selected from the same base population as the
cases? We need to have a clear idea of the base population from
where we are selecting our cases
4. How valid is the measurement of the exposure(s) under
consideration?

ASSESSMENT OF CASE-CONTROL STUDIES cont.…
5. Is the process of selecting the cases and controls independent
from the approach used to get information about exposure?
6. Has the analysis considered the potential role of alternative
explanations to the association under investigation?
7. Are there potential interactions between various factors that the
authors have studied?
8. What is the information value of the published report with
respect to the decision process in health services?

4. Steps in conducting case control study
4.1. Define the case
• It is important that this represent as homogenous a disease
entity as possible
• If nonspecific criteria are used, most but not all people with the disease
will be captured, but many people who do not have the disease will be
included erroneously
• Combination use (sign/sym, physi…..)
• Restrictive vs exclusive (example TB…)—inclusion and exclusion criteria

4.2. select cases
• Case selection will determine decisions on control selection.
• Thus, case definition and selection will affect all the other steps that
follow .
Sources of cases
1. People seeking care
Patients at specific medical care facilities
Hospital discharges
Clinics

Steps cont.…
2. From community and other registries
• Specialized registries
• Other information systems
3. Other sources
• Schools
• Military
• Prepaid Health Plans
• Community Surveillance
• Cases in a cohort—nested

4.2.1.Issues Related to Case Selection
1. misclassification of cases
example BPH
2. Incidence or prevalence
•The problem with use of incident cases is that we must
often wait for new cases to be diagnosed
•a larger number of cases is often available for study while using
prevalent case.
Question: incident or prevalent case is better? Why?

4.2.1.Issues cont.…
Incidence or prevalence
• it is preferable to use incident cases of the disease in case-control studies of
disease etiology.
• These should be all newly diagnosed cases over a given period of time in a
defined population.
• However we are excluding patients who died before diagnosis.
• Prevalent cases do NOT include patients with a short course
of disease.
• So patients who recovered early and those who died will
not be included.

4.2.1.Issues cont.…
3. Exclusion and inclusion criteria
identical exclusion or inclusion criteria must be applied to our definition of
the controls and cases
4. Limited availability of cases
In situations where the disease is very rare, a number of approaches can
be used to make a case-control study is feasible .
we may reconsider the stringency of the diagnostic criteria or we may
think about incorporating in the study cases from broader time periods, a
variety of sources, and locations.
5. etc.….

4.3. Selection of controls
In general, controls should :
Represent the population at risk of becoming cases (controls and
cases should come from the same source population)
The prevalence of exposure among controls should reflect the
prevalence of exposure in the source population.
the time during which a subject is eligible to be a control should be
the time in which the individual is also eligible to be a case

4.3.1. sources of controls
It is addressed in your basic epidemiology
Discus their advantage and disadvantages of the following control sources
1. General population
2. Hospital control
3. Friends/relatives
4. Neighborhood
5. Dead control
6. Hospital visitors
7. Accident victim’s

Characteristics of good control
1. Cases and controls could come from the same population
Case and controls must be similar with
Demographic xic
Cultural background
Socioeconomic
Employment
2. Controls could have theoretical possibility to develop the disease
Example :BPH vs women control
3. Controls could have had an opportunity exposed comparable to cases
The possibility of exposure could not be
typhoid and cholera

Number of control groups
• A single control group is optimal in most of the times.
• However, there are conditions to add more control groups
• when the control is not considered appropriate or when the selected
group has a specific deficiency that could be overcome by inclusion of
another control group
Multiple controls can be:
1. Controls of the Same Type
2. Multiple Controls of Diﬀerent Types

Control-case ratio /controls of the same type
The optimal case-control ratio is 1:1
When the number of cases is small, the sample size for
the study can be increased by using more than one control (e.g. 1:2,
1:3, and 1:4)
What if the ratio is beyond 4???

Controls of the different Type:
we may choose to use multiple controls of different types when we are
concerned that the exposure of the hospital controls used in our study
may not represent the rate of exposure that is “expected” in a
population of non diseased persons .
We may use many controls in the hospital with different cases or from
neighborhood
valuable for exploring alternate hypotheses
Question: Please give one example for multiple control and how you explore alternate hypothesis

Group discussion (15’)
Question 1
• Assume cancer and TB
• 500 case with cancer
• 500 controls(with out cancer)
• 10 % Tb among cases and 20% TB among controls
• Conclusion TB is a protective for cancer?
• What do you feel and what is your expectation for this conclusion?
Question 2
Assume you are going to assess the determinant factors of pneumonia among 2 -59
months age children’s in Bugina district, North Wollo zone, North East Ethiopia, 2018
a. Which case control study design is the most appropriate? Why?
b. which source of control is appropriate? Why?
c. How do you determine your sample size?
d. What is your techniques of sampling? Why?

coffee break (20 minute)
2/22/2020 Dessie 27

Methods for sampling controls
• The controls group may be selected before or after case
ascertainment.
Three main strategies
1. Survivor sampling
2. Case-base or case-cohort sampling
3. Risk set sampling

Survivor sampling
• It is called cumulative density sampling
• When controls are sampled from those people who remained free of
the health outcome until the end of the study period
• Controls cannot ever have the outcome (become cases) when using
this type of sampling
• The controls are called exclusive controls or prevalence controls
• the odds ratio estimates the rate ratio only if the health outcome is
rare
• Is the predominant method for selecting controls in traditional case-
control studies
• Potential survivor bias

Case-base or case-cohort sampling
• select controls from the population at risk at the beginning of the
case diagnosis.
• every person has the same chance of being included as a control
• This is also called inclusive control.
• The odds ratio provides a valid estimate of the risk ratio without
assuming that the disease is rare in the source population

Risk set sampling
• Is called concurrent sampling
• controls are selected from the population at risk as cases are
diagnosed.
• Controls matched to cases by the follow up time
• Note that it is possible that controls must be eligible to become a case
if the health outcome develops in the control at a later time during
the period of observation
two advantages:
1. A direct estimate of the rate ratio is possible.
2. The estimates are not biased by differential loss to follow up
among the exposed vs. unexposed controls.

Group discussion(5’)
• Assume you are going to apply case base or concurrent sampling .
During this procedures , controls have a chance to be case .
a. What do you do for this event?
b. What can you understand for this condition?

Reading assignment
Two stage sampling technique in case control and
method of analysis.

exposure ascertainment
• Potential source of information must be carefully considered in terms of its
ability to provide accurate as well as comparable information for all study
groups.
• Procedures used to obtain information must be similar for cases and
controls
Place and circumstances of interview must be the same.
Blind interviewers or record reviewers, if possible.
Data collectors should be unaware of the specific hypotheses being
tested to reduce observation bias
Etc.….

Sources of exposure data (cases and controls)
• When selecting a particular source, investigators consider its
availability,
its accuracy, and
The logistics and cost of data collection.
• Accuracy is a particular concern in case-control studies
because exposure data are retrospective

Sources of exposure data (cases and controls)
Study subject self-report
Records
Biomarkers-
infrequently used because of difficulty in identifying valid and reliable
markers of exposure to noninfectious agents

Sources of exposure information
Source Type Characteristics
Study subjects(self-
report)
Face-to-face,
telephone,
self-
administer
Can obtain information on many exposures with relative ease &
flexibility;
must be carefully designed & administered to elicit accurate
information;
expensive
Preexisting records Administrative
, regulatory
•May be the only available exposure source;
•avoids bias;
•may be incomplete;
•may lack uniformity & details;
•inexpensive
Biomarkers Levels in
blood, urine,
bone, toenails
Can estimate internal dose;
infrequently used because of difficulty identifying valid & reliable
markers of exposure to noninfectious agents;
expensive

Variants of the case-control design
1. Cumulative (Epidemic) case control studies
2. Nested case-control studies
3. Case-cohort studies
4. case-cross over studies

1. Cumulative (Epidemic) case control studies
• case control studies may address a risk that ends before subject
selection begins.
• For example, a case-control study of an epidemic of diarrheal illness
after a social gathering may begin after all potential cases have
occurred (because the maximum induction time has elapsed)
• an investigator might select controls from that portion of the
population that remains after eliminating the accumulated cases

Case cohort study

Case cohort study
• It is a case control study nested within a cohort in which controls are
selected/sampled at the beginning of the study period (t0)
• cases develop at the same times that were seen in the nested case-
control design, but
• The controls are randomly chosen from the defined cohort with
which the study began.

Why case cohort study other than cohort?(5’)
• Prospective study required large data/participants.
• Data collection process is to expensive and
• Time consuming on all subjects. But,
• In case cohort it saves time and data collection is based on the sub
cohorts not all cohorts.

CC design
• A CC sample consists of a sub cohort, which is a random sample of
the full cohort at (t0), and
• all the subjects with the event (cases).
• Sub cohort's at the beginning are free from disease and a
representative sample.
• The sub cohorts is not time matched to cases, Therefore controls can
be used for many outcome comparisons.
• Final sample size cases outside the sub cohort and inside in the sub
cohort

Sampling of case-cohort

Example

Example
Objective. Investigating the rate of myocardial infarction (MI) associated with the adipose tissue content
Methods: Between December 1993 and May 1997, 160,725 women and men living in the greater Copenhagen
and Aarhus areas were invited to participate in the Danish Diet, Cancer and Health cohort. The criteria for
invitation were the following: age between 50 and 64 years, born in Denmark and no diagnosis of cancer
registered in the Danish Cancer Registry. In total, 57,053 persons (35%) accepted the invitation and were enrolled.
an adipose tissue biopsy was taken from the buttock with the use of a Luer lock system. The samples were flushed
with nitrogen and stored at -80˚C until analysis. which included a random sample (n = 3156) of the total cohort
and all incident MI cases (n = 2148) during follow-up (14 years)
Jakobsen MU et al.

Identification of MI cases
• The study outcome was incident MI (fatal and non-fatal).
• Information on incident cases of MI was obtained by linkage with
nationwide registers.
• How do you think they can select the cases and the controls?

Covariates
• Potential confounders of the association between the adipose tissue
content of TFAs and the rate of MI were selected a priori, based on the
existing literature on risk factors for coronary heart disease, and included
as covariates in the analyses.
• Information on length of education
• Smoking
• leisure time physical activity,
• hypertension and diabetes mellitus was obtained from the lifestyle and
medical history questionnaire.
Jakobsen MU et al.

Example two
• Full cohort
• Sub cohort
• Compare RR

analysis
• Hazard ratios were calculated using Cox proportional hazards
regression with age as the time axis.
• Why they use hazard ratio?

Home take assignment
1. How do you determine sample size for case cohort , cross over and
nested case control study designs
2. Analysis of case cohort, nested and case cross over.
For case cohort come with the following information's
• Weighting
• Borgan II weights
inverse probability weighting (IPW)
• Sampling fraction (considering track of persons inside or outside sub cohort )

Group work(20’)
1. Why we use case cohort over/other than traditional , nested case
control and cohort study
2. Which study design is appropriate for family history and risk of
pregnancy associated breast cancer? Why? How we can apply
3. Adipose Tissue Lipophilic Index and Risk of Ischemic
Stroke (assume it is costive)
NB: for Q#2 &3 the sample is more than 50000

Advantage over nested case control
• An advantage of this design is that because controls are not
individually matched to each case, it is possible to study different
diseases (different sets of cases) in the same case-cohort study using
the same cohort for controls.

Advantages of case cohort
• Save time and money how?
• Ability to estimate risk ratio/rate ratio how?-sample of person not
person-years
Disadvantage
Difficult to weighing procedures used in the analysis compared to other
retrospective study

Thank you

Nested case control

Nested case control
• Nested case-control studies have received increasing attention in the
last few decades
• due to the increased number of large cohorts that have been
established and followed that have permitted selection of cases and
controls for such studies.
• It is designed to sample the cases and controls from the same frame,
the cohort like case cohort
• Thus minimizing the chance of lack of comparability of the cases and
controls

Nested cont.….
• The two designs , however, also differ in one important respect.
• In the case-cohort design the controls are comprised of a random sample
of the cohort at baseline, whereas
• in a nested case-control study, the controls are a random sample of those
in the cohort at the time of diagnosis of each case, and can in addition be
matched to each case on various factors at the time of diagnosis of the
matched case
• The method of control selection in a nested case-control study is thus
incidence density, also known as risk set sampling

Group discussion (3’)
• Example : In a cohort study of risk factors for cancer, Lin et al. (1995) recruited
9775 men. Blood samples were taken and frozen at recruitment into the cohort
study. Over a follow-up of around 7 years, 29 incident cases of gastric cancer
were identified. By this time a number of authors had published studies
suggesting that Helicobacter pylori might be a risk factor for gastric cancer.
• Since H. pylori can be ascertained through an assay on blood samples, Lin and
colleagues decided to exploit their stored samples to test this emerging theory
through a nested case–control study. Between five and eight controls were
sampled for each case, giving 220 controls altogether. Laboratory work was much
reduced compared with analyzing the entire cohort: 249 assays rather than 9775
(less some with missing samples) were required
• How they can check Pylori is a risk factor for gastric cancer?

matching
• Nested case-control studies can be:
1. not matched
2. matched or
3. counter-matched.

Matching in nested cont.….
• Not matched- only time follow up
• Matching:
• Matching cases to controls according to baseline measurements of one or
several confounding variables is done to control for the effect from
confounding variables
• We may match the variables sex,age or residency for cases and controls
• we should beware of the effect of overmatching
• The added bonus here is that no further work is required to obtain
the values of these confounders

Matching cont.….
• counter-matched study:
• When we match cases to controls that have a different baseline risk factor
exposure level.
• it is especially good for assessing the potential interaction (effect
modification!) of the secondary risk factor and the primary risk factor.
• Counter-matched controls are randomly selected from different strata of
risk factor exposure levels in order to maximize variation in risk exposures
among the controls.
• For example, in a study of the risk for bladder cancer from alcohol consumption, you
might match cases to controls who smoke different amounts to see if the effect of
smoking is only evident at a minimum level of exposure
• Question: What is a special condition to apply counter matching?

Strength of NCC
• It can detect differences as statistically significant with a smaller sample size than
that required for a cohort analysis
• Temporal sequence of exposure preceding disease is known and appropriate for
deriving causal inferences.
• Exposure histories are not subject to recall bias because they are determined
before the cases are diagnosed
• Avoids the potential bias of not including fatal cases and may minimize the
potential bias of non-participation,
• The overall cost of the nested case-control approach is less in terms of assessing
the baseline samples
• e.g., serum assays for the subset in the nested case-control study) than an analysis of all the
samples for the entire cohort, as would be the case for a full cohort analysis

NCC cont.….
• Finally, the nested case-control design minimizes selection biases
introduced when cases and controls are not selected from the
same populations

limitations
The nested case-control design shares with the cohort design several
limitations.
• First, data on exposure and/or specimens for exposure analysis must be
collected on the entire cohort at baseline
• Thus, the costs of data collection are likely to be higher than a traditional
case-control study. How ?
• Although the costs of assaying specimens will be lower than for a cohort
study analysis in which all specimens would be assayed
• less suitable for very rare diseases or those with long latent periods, than
for the traditional case control design. How ?

Sampling of nested case control
Sampling of the NCC:
• Study base is some large cohort.
• Select all those who become cases.
• Sampling of controls (incidence density sampling):
• Select controls randomly from those still at risk at time of the case (“risk set”)
• Usually 1 to 4 controls per case (>4 controls only improves efficiency minorly)
• Controls are time-matched to cases.
• Often involves additional matching on confounders.
• Analysis using conditional logistic regression, conditioning on risk set (and
matching strata)
• The odds ratio (OR) estimates the underlying HR in the cohort

Sampling of the NCC cont.….

Group discussion(3’)
:
• Consider a hypothetical cohort study with 100,000 individuals with considering arsenic level of
exposure
• Both groups are enrolled in a study in 1995 and are followed for 10 years until 2005 .The
occurrence of skin cancer is the health outcome of interest .Obtaining a biological measure of
arsenic exposure is quite expensive investigator decides to conduct a nested case-control study
within this cohort .How should the investigator go about selecting controls?
• What type of matching you want to apply?

Case cross over

Case cross over
• it is an epidemiologic technique for assessing the change in risk of an
acute event during a brief interval after exposure to a transient risk
factor
• Was this event triggered by something unusual that happened just
before?” The simple part of the question is “What happened just
before?”
• For example, to find out what might trigger the onset of myocardial
infarction:
• we may wonder if the patient endured certain heavy physical activity, or
• if he/she consumed specific type of food right before the disease.

• In a case-crossover study, this entails answering not just
“What is the population at risk?” but “What are the person times at
risk,
• Which times an outcome could physically happen (under ideal
circumstances of case finding)?
• example
In the collision studies which time could be consider?
the target person times at risk were driving times.

Case cross over
• The exposure level during the case window is then compared
to the exposure level in the control window, a randomly selected time
period of the same length as the case window
• control windows provide the reference level of exposure in the
absence of condition and become the comparison group against
which the exposure in the case window is compared.
•

example
• Objective: To evaluate the association between sleep and wakefulness
duration and childhood unintentional injury.
• Method: case-crossover study, in which each participant acted as his or her
own control. They compared sleep and wakefulness duration in the 24-
hour interval immediately before injury, when the child served as a case,
with the 24-hour interval of the previous day, when the child served as a
control. The dependent variable was the presence or absence of injury. The
exposure categories were obtained dichotomizing daily sleep amount and
length of wakefulness periods. Conditional logistic regression was used to
estimate relative risks (RRs) and 95% confidence intervals (95% CIs). First,
we calculated the RR of injury during a 24-hour period in which the child
had slept <10 hours, compared with a period in which he/she had slept at
least 10 hours.
Valent F. et al.

Example two
Objectives: using a case-crossover design to quantify the relative risk of myocardial
infarction onset after discrete episodes of anger in a patients with confirmed acute
myocardial infarction.
• Methods and Results: We interviewed 1623 patients (501 women) an average of 4 days
after myocardial infarction. The interview identified the time, place, and quality of
myocardial infarction pain and other symptoms, the estimated usual frequency of anger
during the previous year, and the intensity and timing of anger and other potentially
triggering factors during the 26 hours before the onset of myocardial infarction. Anger
was assessed by the onset anger scale, a single-item, seven-level, self-report scale, and
the state anger subscale of the State-Trait Personality Inventory. Occurrence of anger in
the 2 hours preceding the onset of myocardial infarction was compared with its expected
frequency using two types of self-matched control data based on the case-crossover
study design
• The relative risk of myocardial infarction in the 2 hours after an episode of anger was 2.3
(95% confidence interval, 1.7 to 3.2). What can you conclude based on this finding?

exercise (3’) Telephone call and motor collision
• The researchers used case–crossover analysis, a technique for assessing
the brief change in risk associated with a transient exposure.
• According to this method, each person serves as his or her own control;
confounding due to age, sex, visual acuity, training, personality, driving
record, and other fixed characteristics is there by eliminated.
• They used the pair-matched analytic approach to contrast a time period
on the day of the collision with a comparable period on a day preceding
the collision.
• In this instance, case–crossover analysis would identify an increase in risk
if there were more telephone calls immediately before the collision than
would be expected solely as a result of chance

Example cont.….
Question: how we can access the hazard interval for this example?
• Telephone record obtained from drivers phone during the day of
collision for a certain minute and preceding week.
• Then the time of collision was established (hazard interval vs referent)

Exercise from telephone use and motor
collision (20’)
Question 1 based on the given table
• What is the odds of collision when using a
telephone?
• What is the odds of collision when not using
a telephone?
• What is the RR?
• What is your conclusion?
• Possible limitation for this types of study?
Question 2-senario
MI/Shock/death vs spouse death. Which study
design is appropriate
Why? How do you apply?.
Question 3
Risk of unsafe sex following the consumption of
alcohol
Exposureduringhazardinterval/current
Exposure during control
interval/referent
Yes no
yes 13 157
no 24 505

• Four possible scenarios
a. Case period = (EXP +) and Control period = (EXP +)...”concordant”
b. Case period = (EXP +) and Control period = (EXP -)...”discordant”
c. c. Case period = (EXP -) and Control period = (EXP +)...”discordant”
d. d. Case period = (EXP -) and Control period = (EXP -)...”concordant”
 Concordant pairs offer no “information” about the effect of sleep <
10 hours (EXP +) vs. sleep > 10 hours (EXP -)

Terms in crossover
• Referent/control window
• Case/hazard, current period
• Deterrents and triggers for transient effect

Case cross over(another example)
Paired discussion
• MI –sever at the morning
• Who could be the control group?
• what if the control group is general population?
• Describe how do you apply and
• Which type of analysis you are going to use?

Example cont.….
• If you take the controls from general population
• (healthy volunteer bias and health day bias)-because These subjects
would be more likely to decline to be interviewed on stressful days
• ruled out patients hospitalized for other emergencies, because they
would be biased by whatever triggered their car accidents or
gallstone attacks
• Problems to be consider in CCOD-(injuries, adverse drug event ,MI,
car telephone call, lack of sleep the night before, collision after high
speed).

question
• Why Call It “Case-Crossover?”
• What is the difference and similarity between matched case control
and case cross over?
• Trigger,ethiologic factor?
• How you analyze data from case cross over?

Biases in case cross over
1. Incomplete data on the exposure
Objective- compare frequency of exposure in hazard interval to
frequency of exposure to control interval.
Example – take telephone call and motor collision with positive risk.
Overestimate and underestimate
2. Overestimate the exposure immediately prior to the outcome
Imprecision in the onset time. Example repeated call after collision-
overestimate current exposure.
3. Require time period

READING ASSIGNMENT
Case-Time-Control Studies

coffee break (20 minute)
2/22/2020 Dessie 85

matching
• It is defined as the process of selecting the controls so that they are
similar to the cases in certain characteristics, such as
• Age
• Race
• sex
• socioeconomic status, and
• occupation.
• Matching may be of two types:
(1) group matching and
(2)individual matching.

Group Matching
Select controls to get same distribution of variable as cases
(e.g. age group)
 example:
 if 25% of the cases are married, the controls will be selected so that 25% of
that group is also married.
This type of selection generally requires that all of the cases be selected first.
Why?
 After calculations are made of the proportions of certain
characteristics in the group of cases, then a control group, in which
the same characteristics occur in the same proportions, is selected.

Group Matching
• It is useful if distribution of cases for a confounding variable differs
markedly from distribution of that variable in source population

Group Matching
Age Cases Controls
(years) unmatched matched
0-14 45 20 45
15-29 33 20 33
30-44 16 20 16
45+ 6 40 6
TOTAL 100 100 100

example
An investigator wishes to investigate a possible association between
use of calcium channel blockers (drugs used for blood pressure and
heart disease) and Alzheimer’s disease.
• Age is obviously a key confounder: increasing age is associated
with use of the drugs in question and with the onset of Alzheimer’s
disease
• Unmatched controls drawn from the general population will be
younger and hence less likely to be using calcium channel blockers,
leading the crude analysis to overestimate any potential association

Example cont.…
• This can be handled through stratified analysis by age
(e.g. various age categories)
• If unmatched general population controls are used,
there may be few controls in the oldest age strata,
leading to imprecise OR estimates in those strata
(wide confidence intervals)

Individual Matching
Called matched pair
It is carried out one case-at-a-time by sequentially selecting one or more
controls for each case
 in addition to that controls have the same or similar characteristics as the
case on each matching variable.
For example, if we match on age, race, and sex, then the controls for a
given case are chosen to have the same or similar age, race and sex as the
case.
In this approach, for each case selected for the study, a control is selected
who is similar to the case in terms of the specific variables of concern.
 For example, if the first case enrolled in our study is a 45-year-old white
woman, we will seek a 45-year-old white female control

Problem with matching
Two main types of problems with matching
1. Practical and
2. conceptual.
1. Practical problem: the more variables on which we choose to match, the
more difficult it will be to find a suitable control.
2. Conceptual problem : once we have matched controls to cases according
to a given characteristic, we cannot study that characteristic.
 Because in matching according to marital status, we have artificially established an identical
proportion in cases and controls:

Analysis of case control study design
This is the final step in a case control study, and it provides:
1. Exposure rates among cases and controls to the suspected factor
and
2. Estimation of disease risk associated with exposure.

• The goal of matching in case-control studies is to balance the numbers of
cases and controls within strata that will be used for statistical adjustment
purposes.
• When a case–control study (or, indeed, any other type of study) is
matched, the analysis must take account of the matching
• Matched controls are identical to cases with respect to the matching factor.
• Thus, if the matching factor were perfectly correlated with the exposure,
the exposure distribution of controls would be identical to that of cases,
and hence the crude odds ratio would be 1.0

“Matched” vs. “Unmatched” studies
The procedures for analyzing the results of case-control studies differ
depending on whether the cases and controls are matched or
unmatched.
• Unmatched case-control studies are typically analyzed using the
Mantel-Haenszel method or unconditional logistic regression
• Read this article to get some clue:
https://www.bmj.com/content/bmj/352/bmj.i969.full.pdf

Matched
McNamara's test
Conditional logistic regression analysis
Unmatched
Unconditional logistic regression analysis
Chi-square test

Analysis of case control studies
1) Odds Ratio (OR) = ad/bc
2) Attributable proportion among the exposed (APe) or Attributable
Risk Percent = [(OR-1)/OR]x100
3) Attributable proportion in the total population (APt) or Population
Attributable Risk Percent
• APt =[(Pe)(OR-1]/[(Pe)(OR-1)+1]x[100]
• Where Pe is the proportion of exposed controls

Matched Analysis
• Frequency matching: analysis
• Mantel-Haenszel Odds Ratio (weighted)
OR MH= Sum [a d/Ni] for each stratum
Sum [ b c/Ni] for each stratum

Frequency matching: analysis cont…
• keep stratification by age group
0-14 years
Exposed Cases Controls Total
Yes 45(a) 30(b) 75
No 5(c) 20(d) 25
Total 50 50 100(Ni)
ad/Ni = 900/100 = 9
bc/Ni 150/100 1.5

Frequency matching: analysis cont…
15-29 years
Exposed Cases Controls Total
Yes 15(a) 4(b) 19
No 15(c) 26(d) 41
Total 30 30 60(Ni)
ad/Ni / bc/Ni = 390/60 / 60/60 = 6.5/ 1.0
same process for each age group
MH OR = 9 + 6.5 + etc
1.5 + 1.0 + etc

Individual matching: analysis
Analysis in PAIRS:
Controls
Exposed Unexposed
Exposed e f
Cases
Unexposed g h
MH weighted OR =
sum of discordant pairs where case exposed (f)
sum of discordant pairs where control exposed (g)

• frequency and individual matching analysis can also categorized as
the following common types of analysis
1. 1 : 1 Matching
2. 1 : c Matching
3. 1 : Variable matching
4. Many : many matching
5. A modelling approach

1 : 1 Matching
• Is called paired matching
• Each member of the pair is either exposed or unexposed to the risk
factor and is (of course) either a case or a control
• Pairs with the same exposure status for both case and control are
called concordant pairs
• Pairs with different exposures are called discordant

1 : c Matching
• When each case is matched to c controls, a test statistic that
generalizes McNamara's test may be derived using the same
methodology as paired matching.
• Alternatively, the Mantel–Haenszel (MH) approach may be used. Both
approaches give the same results.

Home take assignment
NB: keeping the concept of frequency and individual matching describe briefly the following
method of analysis
1. 1 : Variable matching
2. Many : many matching
3. A modelling approach
Submission date three days before exam

Common biases in case control study
• Selection bias
Self selection bias- refusal or agreement by participants that is related to both the
exposure and disease.
Control selection bias
 Berkson’s bias
Etc.….
• Information bias
Problems of recall
 Limitation in recall and
 Recall bias(rumination bias )
 interviewer bias
Others
What are the mechanisms to minimize these biases?

Reference
1. Ann Aschengrua, George R.Seage. Essential of
Epidemiology in Public Health. Second edition. Bones
and Bartlett. 2008.
2. David G. KleinBaum A pocket Guide to epidemiology
3. Kenneth J. Rothman, Sander Greenland, Timothy L. Lash. Modern
Epidemiology. Philadelphia:Lippincott Williams & Wilkins, 2008, 3rd
edition.
4. Charles H. Hennekens, Julie E. Buring. Epidemiology in Medicine.
Philadelphia:Lippincott Williams & Wilkins, 2008, 3rd edition.
5. Wood ward M. text in statistical science epidemiology study
design and data analysis, 3rd edition 2014
6. Ann Bowling. Research Methods in Health. Investigating Health
and Health Services. Buckingham: Open University Press, 1997

L4. case control study design

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