Meaning of p-value in Medical Research Corresponding Author: Dr. Brijesh Sathian, Assistant Professor & Managing and Chief Editor NJE, Community Medicine, Manipal College of Medical Sciences, Department of Community Medicine, Manipal College of Medical Sciences, 155 - Nepal Submitting Author: Dr. Brijesh Sathian, Assistant Professor & Managing and Chief Editor NJE, Community Medicine, Manipal College of Medical Sciences, Department of Community Medicine, Manipal College of Medical Sciences, 155 - Nepal Article ID: WMC003338 Article Type: Review articles Submitted on:06-May-2012, 05:57:50 PM GMT Published on: 07-May-2012, 04:21:33 PM GMT Article URL: Subject Categories:BIOSTATISTICS Keywords:Medical Research, Testing of Hypothesis, p-value How to cite the article:Sathian B, Sreedharan J. Meaning of p-value in Medical Research . WebmedCentral BIOSTATISTICS 2012;3(5):WMC003338 Copyright: This is an open-access article distributed under the terms of the , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. WebmedCentral > Review articlesPage 1 of 5
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Meaning of p-value in Medical Research Author(s): Sathian B, Sreedharan J
choosing H if the actual observations fall in the critical
region, and choosing H if they do not. More clearly in
large sample test, we will check the calculated value of
the test formula is greater than the tabular value from
Any researcher begins the research with null
the Z- table. Value is 1.96 for 95% and 2.58 for 99%
hypothesis and alternative hypothesis. Null will be for
Confidence Interval. The other method is so called
supporting the old fact and alternative will be for the
software adopted method or widely used method p-
new fact invented/ doubted by the researcher/ scientist.
value. It is described by Cox and Hinkley. Several
Next step is to select one of this scientifically by using
people described p-value in several manners but
the science of statistics. For that the researcher should
finally it is the supporting probability of Null Hypothesis
calculate the likelihood or probability that the
difference observed in the study, however big or small,
could have arisen purely by chance. This probability is
A p-value is a measure of how much evidence we
known as p-value and it is sufficiently small, you can
have against the null hypothesis. The null hypothesis
conclude that you have obtained a statistically
H , represents the hypothesis of no change or no
significant difference. Confidence intervals and
effect, population mean and sample mean equal,
p-values take as their starting point the results
population proportion or sample proportion equal. It is
observed in a study. Crucially, we must check first that
also known as producer’s hypothesis, if customer is
doing research. The smaller the p-value, the more
evidence we have against H . It is also a measure of
how likely we are to get a certain sample result or a
result more extreme, assuming H is true. Medical research involves making a hypothesis and then
“Medicine is a science of uncertainty and an art of
collecting data to test that hypothesis.The p-value
probability”, mused William Osler. Medical journals
measures consistency by calculating the
are a confluence of medicine, science and
probability of observing the results from your
journalism—and are expected to have the values of all
sample of data or a sample with results more
three. Medical journals differ fundamentally from
extreme, assuming the null hypothesis is true. We
scientific journals in that the former is read mainly by
will reject H when p-value is less than 0.05.
practising doctors and not by scientists. Medical
Sometimes, though, researchers will use a stricter
journals will continue to be the main vehicle of
cut-off (e.g., 0.01) or a more liberal cut-off (e.g., 0.10).
scientific information for years to come, particularly
The general rule is that a small p-value is evidence
where access to computer and internet facilities are
against the null hypothesis while a large p-value
relatively limited. Nowadays the output—and
means little or no evidence against the null
rewards— of research are based almost entirely on
hypothesis.
published papers in scientific journals. Scientists in
Suppose that a Viagra medicine company alleges that
low-income and middle income settings want an
only 40% of all patients who take it have a side
opportunity to analyze data for their populations
effect of headache. If, you prescribed Viagra for
according to their own concerns. They want to be in
effective treatment for Erectile Dysfunction and believe
the frontlines of national and global communications
that the adverse event rate is much higher in patients.
about their country’s experiences. The basic
In a sample of 100 patients, all hundred have a
assumption of inferential statistics is that we’re
headache. The data supports your belief because
observing a sample of finite size drawn from a
it is inconsistent with the assumption of a 40%
population that is effectively infinite. By making
headache rate. It would be like tossing a coin 100
observations about the sample, we are trying to make
times and getting heads each time. The p-value, the
generalizations about the population. The
probability of getting a sample result of 100 headache
Neyman-Pearson theory of hypothesis testing
events in all 100 patients assuming that the headache
addresses the problem of choosing between two
event rate is 40%, is a measure of this inconsistency.
statistical hypotheses, H and H . The solution involves
The p-value, 0.00000001, is small enough that we
selecting, before the data are observed, a set of
would reject the hypothesis that the headache event
potential observations (the critical region), then
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rate was only 40%. Researcher see a large p- value,
4. Sackett DL, Richardson WS, Rosenberg W,
he will decide null hypothesis is wrong. But if the
Haynes RB. Evidence based medicine: how to
sample size is not adequate and the sample is not
practice and teach EBM. London: Churchill
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clinically right. So, the researcher should also look
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for one of two things: First one is the power of the test
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which confirms that the sample size in that study was
observa- tional research: chance is not such a fine
adequate for detecting a clinically relevant difference.
Second one is confidence interval that lies entirely
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within the range of clinical indifference. Researcher
Hayward Medical Communications, 2009.
should also be cautious about a small p-value, but for
8. Gardner MJ, Altman DG. Confidence intervals
different reasons. In some situations, the sample
rather than p values: estimation rather than hypothesis
size is so large than required then the researcher can prove the medically insignificant result
9. Last JM. A dictionary of epidemiology. Oxford:
statistically significant [1-30].
International Journal of Epidemiology, 1988.
Consultant is reading a research paper for finding a
10. The Heart Outcomes Prevention Evaluation
better drug for a particular disease. In a good research
S t u d y I n v e s t i g a t o r s . E f f e c t s o f a n
paper author of the research paper should inform you
angiotensin-converting- enzyme inhibitor, ramipril, on
what size difference is clinically relevant and what
cardiovascular events in high-risk patients. N Engl J
sized difference is trivial. But all the manuscripts are
not good. So, the reader has to find out how much of
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a difference would be large enough. Then compare
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this to the confidence interval in the research paper. If
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both limits of the confidence interval are smaller
to the medical literature. II. How to use an article about
than a clinically relevant difference, then
therapy or prevention. B. What were the results
consultant should not change the drug, no matter
and will they help me in caring for my patients?
what the p-value tells.
13. Mittal A , Sathian B, Chandrasekharan N , Lekhi A,
Farooqui M S, Pandey N. Diagnostic Accuracy of
Serological Markers in Viral Hepatitis and Non
Alcoholic Fatty Liver Disease. A Comparative Study in
P-value is a very important concept for any
Tertiary Care Hospital of Western Nepal. Nepal
medical researcher for understanding the research
Journal of Epidemiology 2011;1(2): 60-3. articles published and for making correct
14. Mittal A, Sathian B, Kumar A, Chandrasekharan N,
statistical and medical inferences in his own paper.
Dwedi S. The Clinical Implications of Thyroid
Researcher should not interpret the p-value as the
Hormones and its Association with Lipid Profile: A
probability that the null hypothesis is true. Such an
Comparative Study from Western Nepal. Nepal
interpretation is problematic because a hypothesis is
Journal of Epidemiology 2010; 1(1): 11-6.
not a random event that can have a probability.
15. Sathian B. Methodological Rigors in Medical
Journals from Developing Countries: An Appraisal of
the Scenario in Asia. Nepal Journal of Epidemiology
1 6 . S a t h i a n B , S r e e d h a r a n J , M i t t a l A ,
1. Davies HT. Interpreting measures of treatment
Chandrasekharan N, Baboo NS, Abhilash ES, et.al.
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Case Control Studies in Medical Research. Nepal
2. Guyatt GH, Sackett DL, Cook DJ. Users’ guides to
Journal of Epidemiology 2011;1(3): 77-8.
the medical literature. II. How to use an article about
17. Sathian B. Reporting dichotomous data using
therapy or prevention. A. Are the results of the study
Logistic Regression in Medical Research: The
scenario in developing countries. Nepal Journal of
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Clinical epidemiology: A basic science for clinical
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Mellitus: Risk Factors, Pathophysiology and with its
19. Roy B, Banerjee I, Sathian B, Mondal M, Saha CG.
Clinical Implications: A Hospital Based Case Control
Blood Group Distribution and Its Relationship with
Study in Western Region of Nepal. Nepal Journal of
Bleeding Time and Clotting Time: A Medical School
Based Observational Study among Nepali, Indian and
29. Banerjee I, Roy B, Banerjee I, Sathian B, Mondol
Srilankan Students. Nepal Journal of Epidemiology
M, Saha A. Depression and its Cure : A Drug
Utilization Study from a Tertiary Care Centre of
20. Sreeramareddy CT, Ramakrishnareddy N, Harsha
Western Nepal. Nepal Journal of Epidemiology 2011;1
KumarHN, Sathian B, Arokiasamy JT. Prevalence,
distribution andpredictors of tobacco smoking and
30. Mittal A, Sathian B, Kumar A, Chandrasekharan N,
chewing in Nepal: a secondary data analysis of Nepal
Sunka A. Diabetes mellitus as a Potential Risk Factor
Demographic and HealthSurvey-2006. Substance
for Renal Disease among Nepalese: A Hospital Based
Abuse Treatment, Prevention, and Policy 2011;6:33.
Case Control Study. Nepal Journal of Epidemiology
21. Roy B, Banerjee I, Sathian B, Mondal M, Kumar
SS, Saha CG. Attitude of Basic Science Medical
Students towards Post Graduation in Medicine and
Surgery: A Questionnaire based Cross-sectional Study
from Western Region of Nepal. Nepal Journal of
22. Banerjee I, Roy B, Sathian B, Banerjee I, Kumar
SS, Saha A. Medications for Anxiety: A Drug utilization
study in Psychiatry Inpatients from a Tertiary Care
Centre of Western Nepal. Nepal Journal of
23. Mittal A, Sathian B, Kumar A, Chandrasekharan N,
Farooqui MS, Singh S, Yadav KS. Hyperuricemia as
an Additional Risk Factor for Coronary Artery Disease:
A Hospital Based Case Control Study in Western
Region of Nepal. Nepal Journal of Epidemiology
2 4 . B a s h a A S , M a t h e w E , S r e e d h a r a n J ,
Muttappallymyalil J, Sharbatti AS, Shaikh BR. Pattern
of Blood Pressure Distribution among University
Students in Ajman, United Arab Emirates. Nepal
Journal of Epidemiology 2011;1(3):86-9.
25. Banerjee I, Jauhari AC, Bista D, Johorey AC, Roy
B, Sathian B. Medical Students View about the
Integrated MBBS Course: A Questionnaire Based
Cross-sectional Survey from a Medical College of
Kathmandu Valley. Nepal Journal of Epidemiology
26. Mittal A, Sathian B, Poudel B, Farooqui MS,
Chandrasekharan N, Yadav KS. The Significance of
Hepatobiliary Enzymes for Differentiating Liver and
Bone Diseases: A Case Control Study from Manipal
Teaching Hospital of Pokhara Valley. Nepal Journal of
27. Poudel B, Mittal A, Yadav BK, Sharma P, Jha B,
Raut KB. Estimation and Comparison of Serum Levels
of Sodium, Potassium, Calcium and Phosphorus in
Different Stages of Chronic Kidney Disease. Nepal
Journal of Epidemiology 2011;1 (5): 160-7.
28. Mittal A, Sathian B, Chandrasekharan N, Lekhi A,
Rahib R, Dwedi S. Hepatic Steatosis and Diabetes
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