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

[email protected] [email protected]

Basic Research Competency Program for Research Coordinators August 2015, MEDC, Faculty Of Medicine, Cairo University, Cairo, Egypt.

mailto:[email protected]

mailto:[email protected]

05/02/2023 Professor Tarek Tawfik Amin 2

Objectives “characteristics”

Clear

Complete

Specific

Identify theMain variables to be correlated

Identify the direction of the

relationship+ + + +

Descriptive studies

Correlation studies (experimental and non experimental)

Hypothesis-testing studies


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.

Hypotheses and Underlying Principles

05/02/2023 5Professor Tarek Tawfik Amin


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 conclusionsAbout 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.


HypothesesI- 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 Complexa. 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 VagueNo 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 VagueIt 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 should be stated in writing at the outset of the study.

A single pre-tested hypothesis creates a stronger basis for interpreting the study results than several hypotheses that emerge as a result of data inspection.

Hypotheses that are formulated after data examination are a form of 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”

Hypothesisof difference

Hypothesisof point-

prevalence

Hypothesisof

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 AlternativeI- 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

oThe proposition that there is an association is called the alternate hypothesis.

oThe 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 PopulationPhenomenaOf interest

Actual Subjects

Actual Measure.

Intended SampleIntended variables

RandomSystematic

error

RandomSystematic

error

Research Q

Truth in Universe

Study plan

Truth inthe study

Actual study

Findingsin the study

design

infer

implement

infer


Underlying Statistical PrinciplesStatistical tests Jury 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 noneIncorrect inference (Type II error): there no association when actually there is one.

Innocence: the defendant did not counterfeit moneyGuilt: the defendant counterfeit money

Standard for rejecting innocence: beyond a reasonable doubt.Correct judgment: convict a counterfeiterCorrect judgment: acquit an innocent person

Incorrect judgment: convict an innocent person Incorrect judgment: Acquit a counterfeiter


Type I and type II errorA 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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