Research methodology and biostatistics

dr.rahambacha@yahoo.com 03336422555

dr.rahambacha@yahoo.com
03336422555

Dr. Raham Bacha
Ultrasound specialist
MD, PhD Scholar
MSc Ultrasound (Gold Medalist)
Lecturer Afro-Asian Institute
Lahore
03336422555

Research Methodology
&
Biostatistics.
Respected readers it is mandatory for every researcher to know
somewhat about research and biostatistics. But unfortunately
we have been teach by biostatisticians in our universities and
medical schools. They want to make us biostatistician and teach
us thoroughly. I therefore felt a need to prepare a lecture in
condense form which make enable us to know those terms
which are frequently used in research results.
The purpose of the lecture is to read and understand some
research and even analyze your research data and make
inferences with the help of SPSS software.
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What is Research?
• Research is composed of two worlds.
“Re” mean again
And
Search mean to find new facts
It means to search again new facts or
To modify older ones, in any branch of
knowledge.

Webster international Dictionary
proposed a very inclusive definition.
“A careful inquiry or examination in seeking
facts or principles, diligent investigation in
order to ascertain something.”
Crawford Says:
“Research is simply a systematic and refined
technique of thinking, employing specialized tools,
instruments & procedures in order to obtain a more
adequate solution of a problem than would be
possible under ordinary means.”
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It starts with a problem, collects
data (facts and figures) analyses
these critically based decisions of
actual evidence. It evolves original
work instead of mere exercise of
personal opinion (theory). It is
quantitative and measurements is
therefore a central feature of it.
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• Don’t appreciate the research of other and
yourself.
• Develop critical thinking.
• Specialized tools and instruments (Material
i.e. data sheets)
In fact research is treated as advancement
in knowledge acquired through scientific
methods
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Research provides:
1. Analytic framework for subject matter
investigation
2. Establishes relationship between different
variables e.g. cause and effect
relationship, Co-relationship between
variables.
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Important points
• Research should not be treated as a place
of compilation work. It is not simply the
compilation of material taken from
different books and sources. It is always
expected to something original that
advances some knowledge.
• Research should be very clear in
Researcher mind that he is going to do.
• The domain of Research problem must be
clear.
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STATISTICS
numerical facts in any field of study.
It concerns with collection, organization,
summarization, analysis and drawing
inferences from a data set.
the science comprising methods, which are
used in collection, presentation, analysis,
and interpretation of numerical data
(information).
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Bio-statistics
Bio-statistics is the branch of statistics that concerns
with the applications of statistical methods to
medical and biological data.

In medical field, statistical methods enable us to
check the effectiveness of different testing
modalities in medicines. Recently, it has been
found that applications of statistical methods in
medical data are very effective. Testing of
hypothesis, analysis of variance, chi-square, non-
parametric methods, regression and correlation,
logistic regression etc. are frequently used in the
analysis of health and medical data.

Being medical students often we need to
study research paper or we need to present
our research work in statistical terms. It is
therefor needed to know some of the
fundamental terms frequently used in
research papers.
Significance of Bio-Statistics in Medical.

Central Tendency
Central tendency is a characteristic of a data set
which relates to its average value.
Most commonly used measures are,
 Mean
 Median and mode
 Quartiles
 Deciles
 Percentiles

MEAN
The most commonly used measure of central tendency. It is
the sum of all the observation divided by the number of
observation is mean.
nsobservatioofnumbertotal
setdataofnsobservatiotheallofsum
Mean 

Median
The median of a set of data arranged in order of
magnitude is the middle most value.
Mode
Mode is the most frequently occurring number in the data
set.

Rates
The number of events in a population in specific time.
Suppose, in a specified population “n” events occur
during a fixed period of time n(A). If n(A) of these events
possess some characteristic, say A, then rate of the event
having the characteristic A is given by
𝑹𝒂𝒕𝒆 =
𝒏(𝑨)
𝒏

Prevalence Rate (P.R.)
Prevalence rate of an attribute or event in any group, is the
proportion of individuals in the groups having that
attribute at one point in time. This is also known a
prevalence ratio.
K
groupinsindividualofnumbertotal
timegivenaatdiseaseorattributewithsindividualofnumber
RP .

Incidence Rate (I.R.)
The risk of developing the disease over a period of time is
called incidence rate and is calculated as:
K
groupinsindividualofnumbertotal
timegivenaatofdiseasecasesnewofnumber
RI .

Measures of Dispersion
The measure of spread of data/observations from its
averages. Statistical measures of dispersion are used to
measure the extent to which individual observations
disperse or cluster around the average. two commonly
used measures are;
range and
standard deviation.

Range
Range is the difference between maximum and minimum
values of data set
Standard Deviation
The most widely used and stable measure of dispersion is
the standard deviation. This is a square root of variance.

The most pleasurable moment of my life, when I was awarded with Gold medal

Share feelings with media.

Dr. Raham Bacha Ultrasound Specilist
The Statistical
Profile
25

The Statistical Profile
These include;
1. sensitivity,
2. specificity,
3. positive predictive value, and
4. negative predictive value.
5. accuracy,
6. reliability
Dr. Raham Bacha Ultrasound Specilist 26

These terms are defined as follows:
1. Sensitivity (True Positive Ratio or Rate):
The ability of a test to find disease when disease is present.
2. Specificity (True Negative Ratio or Rate):
The ability of a test to indicate no disease when there is no disease
present (i.e. to exclude disease when a patient is normal.
3. Positive Predictive Value (PPV):
PPV is a measure of how likely it is that disease is actually present
when the test result is positive. In other words, it is the proportion of
people with a positive test who actually have the disease.

These terms are defined as follows:
4. Negative Predictive Value (NPV):
NPV is a measure of how likely it is that disease is actually
absent when the test result is negative. In other words, it is the
proportion of people with a negative test who are free of disease.
5. Accuracy:
The ability of a test to give the correct answer.
6. Reliability:
Consistency in obtaining similar results in similar
circumstances.

The Chi Square Test
This test brings together the statistical terms discussed
above. In the Chi Square, data from any test is compared
to data obtained using the gold standard. In graphical
form, the Chi square looks like this:

The Chi Square Test
Gold Standard result
Our testing
modality
result
present + absent
+
Positive + A B
Negative - C D

The Chi Square Test
Formulas for statistical terms:
1. Accuracy = (A+D)/ A+B+C+D
2. Sensitivity = A/ (A+C)
3. Specificity = D/ (B+D)
4. Positive Predictive Value = A / (A+B)
5. Negative predictive value = D/ (C+D)

Chi Square Example
Let’s take a few moments to work through an example
using the Chi square.
Suppose 100 non-invasive vascular tests were performed in
the vascular lab on patients who also had an arteriogram
(considered the gold standard in this case). The non-
invasive test yielded 55 positive results and 45 negative
results. Of the 55 positive tests the arteriogram found 5 to
be negative and of the 45 negative tests, the arteriogram
found 10 to be positive.

Chi Square Example
Let’s create a Chi square to illustrate the data above.
NON-
INVASIVE
VASCULAR
TEST
Gold Standard
present + absent + Total
Positive + 50 5 55
Negative - 10 35 45
Total 60 40 100

Chi Square Example
The chart above illustrates the results of the 100 tests performed
on our patients.
Note that the 55 total positive exams by the non-invasive test are
broken down to indicate the ones with which the gold standard
agreed and disagreed.
Also note that the total of all four squares must equal the total
number of tests performed (i.e. 100 in our example.
Now let’s perform the calculations required for each of the six
statistical formulas discussed previously.
(Multiply the results by 100 in order to arrive at a percent.)

Chi Square Example
Accuracy = (A+D)/A+B+C+D
= (50+35)/50+5+10+35
= 0.85 x100
= 85%

Chi Square Example
Sensitivity = A / (A+C)
= 50/(50+10)
=50/60
= 0.83
= 0.83x100
= 83%

Chi Square Example
Specificity = D/ (B+D)
= 35/ (5+ 35)
= 35 / 40
=0.88
= 88%

Chi Square Example
Positive predictive value = A/ (A+B)
=50/ (50+5)
= 50/55
=0.91
= 0.91 X 100
= 91%

Chi Square Example
Negative Predictive Value = D/ (C+D)
= 35/ (10+35)
= 35/45
= 0.78
= 78%

Test Goals
The purpose of any of the non-invasive tests discussed in this
course is to identify disease when it is present and exclude it
when it is absent. Whether we are in Search of atherosclerosis or
venous thrombosis, we strive to produce the most accurate result
within our capabilities. In order to confirm or dispute the results
of non-invasive tests, our results are often compared with an
established diagnostic test known as the gold standard. In
cerebrovascular diagnosis, the current gold standard is the
angiogram. In the study of vascular disease, the venogram is still
the gold standard.

Test Goals
The predictive value of a positive or negative test result is
perhaps the most useful expression of accuracy as far as
the referring physician is concerned. It is essential that we
remember that the skill of the vascular technologist may be
crucial in attaining accurate test results. I am sure that is
why we all study so hard to become excellent in the
performance of our examinations.

study
Who knew that statistics could be this much fun!

Research methodology and biostatistics

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