Resrach hypothesis

Hypothesis in research
Professor Tarek Tawfik Amin
Epidemiology and Public Health, Faculty of Medicine, Cairo University
Geneva Foundation for Medical Education and Training
Asian Pacific Organization for Cancer Prevention
amin55@myway.com dramin55@gmail.com
Basic Research Competency Program for Research Coordinators
August 2015, MEDC, Faculty Of Medicine, Cairo University, Cairo, Egypt.

Objectives “characteristics”
Clear Complete Specific Identify the
Main variables
to be correlated
Identify the
direction of the
relationship
+ + + +
Descriptive studies
Correlation studies (experimental and non experimental)
Hypothesis-testing studies
5/7/2016 2Professor Tarek Tawfik Amin

Specific objectives in research
They should include a concise but detailed
description of:
o The intervention (study) to be evaluated,
o The outcome (s) of interest,
o And the population in which the study will be
conducted.

Hypothesis in research:
Objectives
• To recognize the indications, components
and types of research hypotheses.
• Be able to formulate and write a research
hypothesis.
5/7/2016 Professor Tarek Tawfik Amin 4

Hypotheses and Underlying
Principles

Hypothesis definition
A hypothesis is written in such a way that it can
be proven or disproved by valid and reliable data
Grinnel 1988
Hypothesis has certain characteristics:
1. It is a tentative proposition “hunch”
2. Its validity is unknown.
3. In most cases, it specifies a relationship between two or more
variables.

Functions of hypothesis
 Formulation of a hypothesis provides a study with focus
“specific aspects of a research problem to investigate”
 What data are necessary to collect to test the hypothesis.
 Enables you to specifically conclude what is true or what
is false.
Phase I Phase II Phase III
Formulate your
Hunch or
assumption
Collect the
required
data
Analyze data
To draw conclusions
About the hunch-true/false
Process of testing a hypothesis

Hypotheses
It is the further formulation of the study
question into a final and more specific
version, that summarizes
 the elements of the study;
 the sample, the design,
 and the predictor and outcome variables.
The primary purpose is to establish the basis
for tests of statistical significance.

Hypotheses
I- Not needed in descriptive studies describing how
characteristics are distributed in a population.
The prevalence of particular genotype among
patients with hip fracture.
II- Needed in most of the observational and
experimental studies that address statistical
comparison.
The study of weather a particular genotype is
more common in patients with hip fracture
compared to control.

Hypotheses indications
If any of the following terms appear in the
research question, then the study is not
descriptive and a hypothesis should be
formulated:
Greater than, less than, causes lead to,
compared with, more likely than,
associated with, related to, similar to, or
correlated with.

Characteristics of a good research
hypothesis
Simple, Specific, Stated in advance (3Ss)

A-Simple versus Complex
a. Contains one predictor and one outcome variable;
(a sedentary lifestyle is associated with an increased risk of proteinuria in
patients with diabetes).
b. A complex hypotheses contains more than one
predictor;
(a sedentary lifestyle and alcohol consumption are associated with increased
risk of proteinuria in patients with diabetes).

Simple hypotheses
Or more than one outcome variable;
(alcohol consumption is associated with an increased risk of proteinuria and
neuropathy in patients with diabetes).
Complex hypotheses can be readily tested with a
single statistical tests and can be easily approached
by breaking them into two or more simple
hypotheses.

Simple hypotheses
(smoking cigarettes, cigars, or a pipe is
associated with an increased risk of
proteinuria in patients with diabetes).
What type of hypotheses is
this? Simple vs. complex

B-Specific versus Vague
No ambiguity about the subjects, the variables, or
about how the test of statistical significance will be
applied.
it uses concise operational definitions that
summarize the nature and source of the subjects and
how variables will be measured;

(a history of using tricyclic antidepressant
medications, as measured by review of
pharmacy records, is more common in
patients hospitalized with an admission
diagnosis of myocardial infarction at
Longview Hospital in the past year than in
control hospitalized for pneumonia).

Specific versus Vague
It is often obvious from the research hypothesis
whether the predictor variable and the outcome
variable are dichotomous, continuous, or
categorical.
(alcohol consumption (in mg/day) is associated with an increased risk
of proteinuria (> 30 mg/dL) in patients with diabetes).

C-In Advance versus After-the-Fact
The hypothesis shouldbe statedin writing at the outset
of the study.
A single pre-testedhypothesis creates a stronger basis
for interpreting the study results than several
hypotheses that emerge as a result of data inspection.
Hypotheses that are formulatedafter data examination
are a formof multiple hypothesis testing that often
leads to over-interpreting the importance of the
findings.

Types of hypothesis
Alternate hypothesis
Null hypothesis
Research hypothesis
Hypothesis
of no difference
“null hypothesis”
Hypothesis
of difference
Hypothesis
of point-
prevalence
Hypothesis
of association

Types of research hypothesis “examples”
There is no significant difference in the proportion
of male and female smokers in the study
population. Hypothesis is ?
A greater proportion of females than males are
smokers in the study population. Hypothesis is ?
A total of 60% of females and 30% of males in the
study population are smokers. Hypothesis is ?
There are twice as many female smokers as male
smokers in the study population. Hypothesis is ?

• To address the existing gap in the literature on smoking
among adolescents we have tested the following
hypotheses:
• First, older male adolescents are more likely to smoke
tobacco than younger and female adolescents.
• Second, smoking among close relatives (environmental
tobacco exposure) and friends (peer pressure) would
increase the likelihood (risk) of being current smoker.
• Finally, certain motives (socializing, imitation, outing,
rather than relieve of stress and pleasure) and the
presence of depressive and/or anxiety disorders may
represent potential predictors for the current smoking
status among adolescents.
Writing a hypothesis: examples

• We specifically hypothesized that adolescents with SCD
would have decreased mean scores along the different
subscales of the HRQoL measure compared to adolescents
without SCD.
• We also predicted that certain demographic factors
(increasing age, gender, low socio-economic status)
would be related to HRQoL with males and adolescents
from lower SES backgrounds reporting lower quality of
life.
• Additionally, we predicted that adolescents with SCD
who experienced disease-related complications, frequent
pain episodes, and greater health care utilization would
report lower quality of life than adolescents with SCD
who did not report these factors.

• We hypothesized that vitamin D level is
altered in healthy obese adults (aged 18-25
yrs) which may predispose them to the
development of secondary
hyperparathyroidism and alteration of insulin
resistance compared to lean age and gender
matched peers.

Types of Statistical Hypotheses

1- Null and Alternative
I- The null hypothesis states that there is no association
between the predictor and outcome variables in the
population.
(there is no difference in the frequency of drinking well
water between subjects who develop peptic ulcer disease
and those who do not).
II- It is the formal basis for testing statistical
significance.
Statistical tests help to estimate the probability that an
association observed in a study is not due to chance.

Null and Alternative
o The proposition that there is an association is
called the alternate hypothesis.
o The alternative hypothesis cannot be tested
directly; it is accepted by default if the test of
statistical significance rejects the null
hypothesis. “accepted when null is rejected”

2- One and Two-sided
I- A one-sided hypothesis specifies the direction of the
association between the predictor and the outcome
variables.
Drinking well water is more common among subjects
who develop peptic ulcer (one-sided).
II- A two-sided hypothesis states only that an
association exists;does not specify the direction.
The prediction that subjects who develop peptic ulcer
disease have a different frequency of drinking well water
than those who do not (two-sided).

Indications
For one-sided:
 When only one direction for an association is
important or biologically meaningful (a new
drug for hypertension is more likely to cause
rashes than a placebo).
 When there is good evidence from prior studies
that an association is unlikely to occur in one of
the two directions (smoking affects the risk of
brain cancer).

Underlying Statistical Principles
Target
Population
Phenomena
Of interest
Actual
Subjects
Actual
Measure.
Intended
Sample
Intended
variables
Random
Systematic
error
Random
Systematic
error
Research Q
Truth in
Universe
Study plan
Truth in
the study
Actual study
Findings
in the study
design
infer
implement
infer

Underlying Statistical Principles
Statistical testsJury decision
Null hypothesis: there is no association between dietary
carotene and incidence of colon cancer.
Alternative hypothesis: there is an association between
dietary carotene and colon cancer incidence.
Standard for rejection null hypothesis:
Level of statistical significance ( ≤ 0.05)
Correct inference: conclude an association when one does
not exist in the population.
Correct inference: no association between carotene and
colon cancer when one does not exist
Incorrect inference (Type I error): association in the
study when actually is none
Incorrect inference (Type II error): there no association
when actually there is one.
Innocence: the defendant did not
counterfeit money
Guilt: the defendant counterfeit
money
Standard for rejecting innocence:
beyond a reasonable doubt.
Correct judgment: convict a
counterfeiter
Correct judgment: acquit an
innocent person
Incorrect judgment: convict an
innocent person
Incorrect judgment: Acquit a
counterfeiter

Type I and type II error
A type I error (false-positive) occurs if the
investigator rejects a null hypothesis that is
actually true in the population.
A type II error (false-negative) occurs if the
investigator fails to reject a null hypothesis that is
actually not true in the population.

Truth in the population Vs. the results
in the study sample (the four possibilities).
Truth in the population
No association between
predictor and outcome
Association between
predictor and outcome
Results in the study sample
Type I error
Correct
Correct
Type II error
Reject null hypothesis
Fail to reject null

, and Power
 The probability of committing a type I
error (rejecting the null when it is
actually true) is called  (alpha),
another name is the level of statistical
significance.
 An  level of 0.05, setting 5 % as
the maximum chance of
incorrectly rejecting the null
hypothesis.


 The probability of making a type II error (failing to reject
the null hypothesis when it is actually false) is called 
(beta).
 The quantity (1-  ) is called power, the probability of
rejecting the null hypothesis in the sample if the actual
effect in the population equals effect size.
 If  is set at 0.10, we are willing to accept a 10 % chance of
missing an association of a given effect size. This
represents a power of 90 % (there is 90 % chance of
finding an association of that size).

P Value
 A ‘non significant’ result (i.e., one with a P value
greater than ) does not mean that there is no
association in the population, it only means
that the result observed in the sample is
small compared with that occurred by
chance alone.
 Those with hypertension were twice as likely to
develop cancer prostate compared to
normotensive subjects (P of 0.08)

Thank you

Resrach hypothesis

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