research methodology and biostatistics.pptx

TABLE OF CONTENTS
 Introduction
 Objectives of research
 Types of research
 Research process
 Sampling designs
 Methods of data collection and presentation
 Study designs
 Review of literature
 Hypothesis
 Interpretation and report

WHAT IS RESEARCH?
 Research is the
continual search for
truth using the
scientific method.

OBJECTIVES OF RESEARCH
• To gain familiarity with a phenomenon or to
achieve new insights into it.
• To portray accurately the characteristics of a
particular individual, situation or a group.
• To determine the frequency with which something
occurs or with which it is associated.
• To test a hypothesis of a causal relationship
between variables.

Descriptive vs.
Analytical
Applied vs.
Fundamental
Quantitative vs.
Qualitative
Conceptual vs.
Empirical
Types of
Researc
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 Identify & Define the problem- Essentially two
steps are involved in defining research problem
a. Understanding the problem thoroughly
b. Rephrasing same into meaningful terms
from a point of view
 Review the literature- Once the problem is
defined a brief summary of it should be written
down.

 Formulate the hypothesis- It is tentative
assumption made in order to draw and test its
logical or empirical consequences, it should be
very specific and limited to the piece of research.
 Design the research-The function of research
design is to provide for the collection of relevant
evidence with minimal expenditure of effort, time
and money.

 Collect the data - Ways to collect the data like
observation, through personal interview,
telephone interview, by questionnaires.
 Analyse the data
 Interpretation and report

SAMPLING DESIGNS
• The study population is too large and it may be too
expensive and time consuming to attempt either a
complete or nearly complete coverage in a statistical
study, so we take a sample from the population.
• Sample is the representative of the population and to
ensure that we chose each unit of the sample
technically, the process is called sampling technique.
• Sufficient sample size is calculated based on the
precision of estimate of sample and approximate
prevalence of disease.

research methodology and biostatistics.pptx

Judgment
• Choosing the sample items depends
on the judgment of the investigator.
• Samples are because the
investigator believes that they are
typical or representative of the
population under his/her study.
• Example:
A researcher studying implant
success rates selects only
experienced prosthodontists to
answer a survey, believing they
provide the most reliable insights.

Convenience sampling
• It is a matter of taking what you can get.
• It is an accidental sample and not randomly
obtained.
• Example:
A dentist wants to study denture satisfaction, so
they only survey patients who visit their clinic
instead of selecting people from the whole city.

QUOTA SAMPLING
• Most commonly used in non probability sampling.
• Quotas are set up according to some specified
characteristics.
• Done to ensure the inclusion of a particular
segment of the population.
• Example:
A researcher wants to study denture satisfaction
and ensures the survey includes 50 men and 50
women

SNOWBALL SAMPLING
• A special non probability method used when the
desired sample characteristic is rare.
• Snowball sampling relies on referrals from initial
subjects to generate additional subjects.

SNOWBALL SAMPLING - STEPS
 Make contact with one or two cases in
the population.
 Ask these cases to identify further
cases.
 Ask these new cases to identify
further new cases.
 Stop when either no new cases are
given or the sample is as large as is
manageable.

SIMPLE RANDOM SAMPLING
• It is applicable when:-
The population is small, available
and homogenous.
• This is done either by using table of random
numbers or lottery method.
• The principle used to select the sample is each
and every unit will have equal chance of getting
selected.

STRATIFIED RANDOM SAMPLING
This sampling technique is applicable when:-
• The population is large and heterogeneous.
• First the population is divided into homogenous
group called strata, and the sample is drawn from
each stratum at random in proportion to its size.
• This gives greater accuracy result. (Best sampling
procedure that can be followed)

SYSTEMATIC SAMPLING
• Selecting first unit at random.
• Selecting additional units at evenly spaced
intervals.
• Complete list of population is available.

CLUSTER SAMPLING
• This method is used when the population forms
natural groups or clusters, such as villages, ward
blocks or school children etc.
• Here simple random sampling is selected not of
individual subjects, but of groups or clusters of
individuals.
• The sampling units are clusters and sampling
frame is a list of these clusters.

STRATIFICATION V/S CLUSTERING
Stratification Clustering
All strata are represented in
the sample.
Only a subset of clusters are
in the sample.
Less error compared to
simple random.
More error compared to
simple random.
More expensive to obtain
stratification information
before sampling.
Reduces costs to sample
only.

Multistage random sampling
MULTI STAGE SAMPLING
• The first stage is to select the groups or clusters.
• Then subsamples are taken in as many subsequent
stages as necessary to obtain the desired sample
size.
• Example:
For a survey some schools are selected randomly →
from which classes were selected randomly from
→
which sections were selected randomly from which
→
students were selected randomly

MULTI PHASE SAMPLING
• Part of the information collected from whole
sample & part from subsample.
• Example:
In Tb survey MT in all cases– Phase I
X–Ray chest in MT+ve cases– Phase II
Sputum examination in X –Ray +ve cases - Phase III
• Survey by such procedure is less costly, less
laborious & more purposeful

Feature Probability Sampling Non-Probability Sampling
Definition
A sampling method where every
member of the population has a
known, non-zero chance of being
selected.
A sampling method where some
members of the population have
no chance of being selected, and
selection is based on subjective
judgment.
Selection Basis Random selection
Non-random selection
Bias Low bias due to randomness Higher risk of bias
Applicability Used in large-scale, formal
research where generalization is
needed
Used in exploratory research,
qualitative studies, and when
probability sampling is
impractical
Complexity More complex and time-
consuming
Easier and quicker to conduct
Use Case Suitable for statistical research,
surveys, and experiments
requiring accuracy
Suitable for preliminary studies,
market research, and hard-to-
reach populations

TYPES OF DATA
• Data is collective recording of observations either numerical or
otherwise.
• Demographic data comprise details of population size, geographic
distribution, ethnic groups, socio-economic factors and their trends
over time.
• Types:
1. Qualitative Data: The data collected on the basis of attributes or
qualities like sex, malocclusions, cavity etc.
2. Quantitative Data: The data collected through measurement using
calipers, like bone height, bone width etc. It is further classified into
two types
a) Discrete: When variable under observation takes only fixed values like
whole numbers, the data is discrete.
b) Continuous: If the variable can take any value in a given range,
decimal or fraction, the data is continuous.

COLLECTION OF DATA
• Data can be collected through:
a) Primary source: Data collected is obtained by the investigator himself.
This is the first hand information. Primary data can be obtained by one of
the following methods:
1. Direct personal interview: There is face-to-face contact with the persons
from whom the information is to be obtained.
The advantage of this method is that all the information can be
collected accurately and any ambiguity can be clarified.
2. Oral health examination: It is used when information on oral health
status is needed. It is conducted by dentists and dental auxiliary personal.
3. Questionnaire method: A list of questions pertaining to the survey known
as questionnaire is prepared and the various informants are requested to
supply the information either personally or through post.
b) Secondary source: The data already recorded is utilized to serve the
purpose of the objective of the study. Eg: the records of OPD of dental
clinics.

PRESENTATION OF DATA
• Data collected and compiled from experimental work,
surveys, registers or records are raw data. These are
unsorted and difficult to understand.
• The data is sorted and classified into characteristic groups
or classes.
• The objective of classification of data is to make the data
simple, concise, meaningful, interesting and helpful in
further analysis.
• There are two main methods of data presentation:
a. Tabulation
b. Charts and diagrams

a) Tabulation
• Tables are simple devices used for presentation of data.
• Types of tables:
i. Master table: They are the tables which contain all the
data obtained from a survey.

ii. Simple table
These are one way
tables which supply
answers to questions
about one
characteristic of data
only.

iii. Frequency distribution
table
• The simplest table is a
two-column frequency
table.
• The first column lists
the classes into which
the data are grouped.
• The second column
lists the frequencies
for each classification.

b) Charts and Diagrams
• Charts and diagrams are one of the most convincing and
appealing ways of depicting statistical results.
• Diagrams and graphs are extremely useful because:
1) They are attractive to the eyes,
2) They give a bird’s eye view of the entire data
3) They have a lasting impression on the mind of the layman
4) They facilitate comparison of data relating to different
time periods and regions.

 Bar chart
A. Simple bar chart
• It represents only one
variable.
• Eg: Age-wise
prevalence of dental
caries (in percentage)

B. Multiple bar chart
• This diagram is similar
to bar diagram except
that for each category
of the variable there
are a set of bars of the
same width
corresponding to the
different sections
without any gap in
between.
• Eg: Prevalence of
dental caries based on
age and gender.

C. Proportional/
component bar chart
• The individual bars are
divided into two or
more parts.
• This diagram is used to
compare the sub-groups
between different
major groups of
observation.
Eg: Prevalence of dental
caries based on age and
gender.

Pie diagrams/ charts
• The entire graph looks
like a pie and its
components represent
slices cut from a pie.
• The total angle at the
centre of a circle is
equal to 360 degree and
it represents the total
frequency.
• Eg: distribution of
dental disease in 30-40
yr old

Line diagrams
• This diagram is useful to
study the changes of values
in the variable over time
and is the simplest of all
diagrams.
• On the X-axis, the time
such as hours, days, weeks,
moths or years are
represented and the value
of any quantity pertaining
to this is represented along
the Y-axis.
• Eg: Age-wise prevalence of
dental disease

Histogram
• Pictorial diagram of
frequency distribution.
• No space between the
cells on a histogram.
• Class intervals on X-axis
and the frequencies on
Y-axis.
• Eg: Age-wise prevalence
of dental caries.

Frequency polygon
• Here a point is marked
over the mid-point of
the histogram blocks.
Following points are
connected by straight
lines.
• Eg: Age-wise prevalence
of dental caries.

Cartogram/Spot
map/ Shaded map
• These maps are used to
show geographical
distribution of
frequencies of a
characteristic.
• Eg: coverage of cases of
oral cancer by
geographic area may be
depicted through a dot
or point- spot map and
if shades are used –
shaded map.

Pictogram
• Small pictures or
symbols are used for
presenting data.
• They are especially used
for common man.
• Eg: Population per
physician.

Scatter Diagram
• It shows the relationship
between two variables.
• If the dots cluster around
a straight line, it shows a
linear relationship.
• Eg: Relationship between
sugar intake( x-axis) and
dental caries prevalence
(y-axis),showing a
positive relationship.

EPIDEMIOLOGY
 The study of the distribution and determinants of
health related states or events in specified
populations, and the application of this study to
the control of health problems.
 Given by John M Last in 1988.

Aims of epidemiology
Epidemiology has three main aims:
a. to describe the size and distribution of disease
problems in human populations
b. to identify aetiological factors (risk factors) in the
pathogenesis of disease; and
c. to provide the data essential for the planning,
implementation and evaluation of services for the
prevention, control and treatment of disease.

Levels of Prevention
 1. Primordial : It is the prevention of the emergence or development
of risk factors in which they have not yet appeared
 2. Primary : It is the action taken prior to onset of disease, which
removes the possibility that a disease will ever occur. Primary level of
prevention is applied when risk factors are present but disease has
not yet taken place
 3. Secondary : It halts the progress of disease at its incipient stage
and prevents complications
 4. Tertiary : Is applied when disease has advanced beyond early
stages. It aims to reduce or limit impairments and minimize suffering
caused by existing departures from good health

Descriptive Epidemiologic Studies
 Descriptive studies are usually the first phase of an
epidemiological investigation. These studies are
concerned with observing the distribution of disease or
health-related characteristics in human populations and
identifying the characteristics with which the disease in
question seems to be associated.
 Such studies basically ask the questions.
a. When is the disease occurring ? - time distribution
b. Where is it occurring? - place distribution
c. Who is getting the disease? - person distribution

Analytical Epidemiologic Studies
• Analyzing relationships between health status and
other variables.
• The objective is testing the hypothesis.
• Subject of interest is individual, but inference is
applied to population.
TYPES
1. Case-control studies.
2. Cohort studies.

Case-control studies
It is first approach to testing
causal hypothesis, especially
for rare disease.
Three features-
 Both exposure and
outcome (disease) has
occurred.
 Study proceeds backwards
from effect to cause.
 It uses a control group to
support or refuse an
inference.

Basic steps in Case-control study
1. Selection of cases and controls
• CASES
- Case definition – (Diagnostic criteria and Eligibility criteria.)
- Source of Cases – (Hospital or General population)
• CONTROLS
- Free from the disease under study.
- Similar to the cases in all other aspects.
- Source- Hospital, Relative, Neighbourhood, General population
2. Matching.
• Matching is process for selecting controls in a manner that they
are similar to cases in all variables.
• Matching is essential for comparability and for elimination of
confounding bias.

• A Confounding factor is a factor which associated with both exposure and disease and unequally distributed in
study and control groups.
• Matching procedure–
- Group matching (control group is similar to cases in overall distribution of matching factors such as age, gender
etc.)
- Pair matching.(each case selected – one or more control with similar characteristics)
3. Measurement of exposure.
• Information of exposure of risk factor should be obtained in same manner for both cases and controls.
• Estimation of exposure rate can be reported by Questionnaire, Interviews and Hospital records.
4. Analysis and interpretation
1. Exposure rates
Estimation of rates of exposure of suspected factor among cases & controls.
2. Odds Ratio
 Measure of exposure – disease association is relative risk
 Since case control study is not one of a prospective design, it is impossible to generate true incidence ratio
between exposed v/s non exposed group.
 Indirect method of estimating relative risk was called as Odds ratio

Thalidomide Tragedy
A classic example of Case-control study
• A classic example of a case-control study was the discovery of
the relationship between thalidomide and limb defects in babies
born in the Federal Republic of Germany in 1959 and 1960.
• The study, done in 1961, compared affected children with
normal children.
• Of 46 mothers whose babies had malformations, 41 had been
given thalidomide between the fourth and ninth weeks of
pregnancy, whereas none of the 300 control mothers, whose
children were normal, had taken the drug during pregnancy.
• Accurate timing of the drug intake was crucial for determining
relevant exposure.

Cohort Studies
• Cohort is group of people
with similar
characteristics.
• Also called follow-up or
incidence studies.
• Begin with a group of
people who are free of
disease.
• Whole cohort is followed
up to see the effect of
exposure.

Types of Cohort Studies
1. Prospective cohort studies. (Currents cohort study)
2. Retrospective cohort studies. (Historical cohort study)
3. Combination of retrospective and prospective cohort studies.
 While retrospective cohort studies try to compare the risk of
developing a disease to some already known exposure factors, a
case-control study will try to determine the possible exposure
factors after a known disease incidence.
 Elements of Cohort studies
1. Selection of study subjects.
2. Obtaining data on exposure.
3. Selection of comparison group.
4. Follow-up.
5. Analysis.

1. Selection of study subjects.
• General population( heterogeneity of exposure to susceptible etiological factor )
• Special group (Doctors, Tyre industry workers; unusual exposure to a suspected causative factor)
• Cohort should be selected from the group with special exposure under study.
2. Obtaining data on exposure.
 Information obtained from
1. Cohort members- questionnaire, interview.
2. Review of records.
3. Medical Examination or special tests on cohort members.
4. Testing or evaluation of environment within which cohort members have lived
5. Information about exposure (or any other factor related to the development of the disease being investigated)
should be collected in a manner that will allow classification of cohort members
6. Categorized according to exposure –
• Whether exposed or not exposed to special causal factor.
• Degree of exposure.

3. Selection of comparison group.
1. Internal comparison - Subjects are categorized in group according to degree of exposure& mortality and morbidity compared.
2. External comparison - When degree of exposure not known.
Control group with similar in other variable.
3. Comparison with general population - Comparison with the general population as exposed group.
4. Follow-up.
• Regular follow-up of all participants.
• Measurement of variable depends upon outcome.
Procedure-
1. Periodical medical examination.
2. Review of hospital records.
3. Routine surveillance and death records.
4. Mailed questionnaire and phone calls.
5. Analysis.
• Data are analyzed in terms of –
a. Incidence rates- In a cohort study, we can determine incidence rates directly in those exposed and those not exposed
b. Estimation of risk.
• Relative Risk.
• Attributable Risk.

Case control study Cohort study
1. Preceeds from effect to cause 1. Preceeds from cause to effect
2. Starts with disease 2. Starts with people exposed to risk factors
3. Tests whether the suspected factor is
associated more with the diseased
3. Tests whether the disease occur more in those
who are exposed to risk factors
4. First approach to testing the hypothesis 4. Reserved for precisely formulated hypothesis
5. Suitable for rare disease 5. Inappropriate when fewer subjects are
involved
6. Only estimates odds ratio 6. Estimates relative risk and attributable risk
7. Relatively inexpensive 7. Expensive

EXPERIMENTAL EPIDEMIOLOGY
• Interventional or experimental study involves attempting to
change a variable in subjects under study.
• This could mean the elimination of a dietary factor thought
to cause allergy, or testing a new treatment on a selected
group of patients.
• The effects of an intervention are measured by comparing
the outcome in the experimental group with that in a
control group.
 Types of Experimental Studies
1. Randomized Control Trials.
2. Field Trials
3. Community Trials.

Randomized Control Trials (RCT)
• RCT is a planned experiment designed to asses the efficacy of
an intervention in human beings by comparing the effect of
intervention in a study group to a control group.
• The allocation of subjects to study or control is determined
purely by chance (randomization).
• For new programme or new therapy RCT is best method of
evaluation.
 Basic Steps in RCT
1. Drawing-up a protocol.
2. Selecting reference and experimental population.
3. Randomization.
4. Manipulation or Intervention.
5. Follow-up.
6. Assessment of outcome.

1.The Protocol - Study conducted under strict protocol.
• Protocol specifies - aim, objectives, criteria for
selection of study and control group, sample size,
intervention applied, standardization and schedule
and responsibilities.
• Pilot study - some time small preliminary study is
conducted to find out feasibility or operational
efficiency.

PILOT STUDY
 A pilot study is the first step of the entire research
protocol and is often a smaller-sized study assisting in
planning and modification of the main study.
 Before a pilot study begins, researchers must fully
understand not only the clear purpose and question of the
study, but also the experimental methods and schedule.
 Researchers become aware of the procedures involved in
the main study through the pilot study, which aids in the
selection of the research method most suitable for
answering the research question in the main trial.
 Despite the benefits and importance of the pilot study,
researchers often are not interested.
Korean J Anesthesiol 2017 Dece
70(6): 601-605

OBJECTIVES OF PILOT STUDY
 Feasibility of the study protocol : A pilot study replicates the
main study's procedures to assess feasibility, including
participant criteria, drug preparation, intervention,
instrument testing, and researcher training. It ensures
smooth execution before the main study begins.
 Randomization and blinding : A pilot study assesses if the
randomization and blinding are appropriately executed.
 Recruitment and consent :A pilot study assesses consent
form validity, recruitment rates, researcher needs, and
consent processing time. Identifying the recruitment rate is
crucial, as insufficient participants can reduce statistical
power and risk trial termination.
70(6): 601-605

 Acceptability of intervention : A pilot study assesses the
feasibility, acceptability, and potential benefits of a study
drug or intervention. It ensures participants are willing to
accept the intervention before proceeding with the main
study.
 Sample size calculation : One of the key reasons why a
pilot study is needed is to obtain the required preliminary
data for the calculation of a sample size for the primary
outcome.
To conclude a pilot study provides necessary information not
only for calculating the sample size, but also for assessment
of all other aspects of the main study, minimizing
unnecessary effort from the researchers and participants, as
well as the dissipation of research resources.
70(6): 601-605

2. Selecting Reference and Experimental population
•Reference population (Target Population)
1. Is the population in which the results of the study is
applicable.
2. A reference population may be – Human being, country
specific, age, sex, occupation etc.
•Experimental Population (Study Population)
1. It is derived from the target population.
2. Three criteria-
a. they must be representative of RP.
b. qualified for the study.
c. ready to give informed consents.

3. Randomization
• It is statistical procedure to allocate participants in groups –
Study group and Control group.
• Randomization gives equal chance to participants to be
allocated in Study or Control group.
• Randomization is an attempt to eliminate ‘bias’ and allow
‘comparability’.
• Randomization eliminates ‘Selection Bias’.
• Randomization is best done by the table of random numbers.
• In Analytical study there is no randomization, we already study
the difference of risk factor. So only option is Matching.

4. Manipulation or Intervention
• Manipulation by application of therapy or reduction or
withdrawal of suspected causal factor in Study and control
group.
• This manipulation creates independent variable whose
effect is measured in final outcome.
• The independent variable is the value which is
manipulated in an experiment. The dependent variable is
the value observed by the researcher during an
experiment.

5. Follow-up
• Follow-up of both study and control group in standard manner in
definite time period.
• Duration of trial depends on the changes expected in duration since
study started.
• Some loss of subjects due to migration, death is k/as Attrition.
6. Assessment
• Final step is assessment of outcome in terms of positive and negative results.
• The incidence of positive and negative results are compared in both group-
Study group and Control group.
• Results are tested for statistical significance. (p value)

FIELD TRAILS
• Field trials, in contrast to clinical trials, involve people
who are healthy but presumed to be at risk.
• Data collection takes place “in the field,” usually among
non-institutionalized people in the general population.
• Since the subjects are disease-free and the purpose is to
prevent diseases.

COMMUNITY TRIALS
• In this form of experiment, the treatment groups
are communities rather than individuals.
• This is particularly appropriate for diseases that
are influenced by social conditions, and for which
prevention efforts target group behaviour.
• Example–
IDD and Iron def Anaemia.

REVIEW OF LITERATURE
 For any specific research work to occupy the place in
development of discipline the researcher must be
thoroughly familiar with both previous Theory and
research
 In research methodology the term literature refers to the
knowledge of particular area of Investigation of any
discipline which includes theoretical practical and its
research studies
 Review of literature include critical analysis and
integration of information from various sources

Purpose of literature Review-
 Find out what information already exists in field Of
research
 Show relationship between previous studies or theories
 Provide a context for your own research
 Identify main ideas conclusions and theories and establish
the similarities and differences
 Identify main methodology and research techniques
 Identify major gaps in literature

Sources of literature-
Sources of literature-
 Primary source- All sources are original and they provide
first hand information. It include dissertations, diaries,
interviews, notes, patents, studies or surveys, technical
reports etc.
 Secondary source- It is a source that provides non original
or second hand data or information secondary sources are
written information about the primary sources. It include
dictionaries, encyclopaedia, government policy,
handbooks public opinion and reviews etc.

SYSTEMATIC REVIEW
 Systematic review is all about relevant empirical evidence
in order to provide a complete interpretation of research
result
 One must adopt a comprehensive objective and
reproducible search strategy to capture all relevant
resources of evidence
 In doing so you can be confident of having incorporated all
the appropriate material for the topic at hand
 A thorough search strategy involve multiple databases
source of grey source of literature, conference
proceedings and abstract

Benefits-
 They provide clear and comprehensive overview of
available evidence on a given topic.
 It helped to identify research gaps in current
understanding of field.
 They can highlight methodological concern in the research
studies that can be used to improve future work in this
topic area.
 They can also use to identify questions for which the
available evidence provide clearances and thus far which
further research is not necessary.

META-ANALYSIS
 Glass first defined meta-analysis in the social science
literature as “The statistical analysis of a large collection
of analysis results from individual studies for the purpose
of integrating the findings”.
 Meta-analysis is a quantitative, formal, epidemiological
study design used to systematically assess the results of
previous research to derive conclusions about that body of
research.
 Meta-analyses are conducted to assess the strength of
evidence present on a disease and treatment.
Meta-analysis in medical research Haidich AB
Department of Hygiene and Epidemiology,
Aristotle University of Thessaloniki School of

 One aim is to determine whether an effect exists; another
aim is to determine whether the effect is positive or
negative and, ideally, to obtain a single summary estimate
of the effect.
 The results of a meta-analysis can improve precision of
estimates of effect, answer questions not posed by the in-
dividual studies, settle controversies arising from appar-
ently conflicting studies, and generate new hypotheses.
 Conducting a meta-analysis involves systematically
synthesizing data from multiple studies to derive
comprehensive insights.
Meta-analysis in medical research Haidich AB
Department of Hygiene and Epidemiology, Aristotle
University of Thessaloniki School of Medicine,

Steps in conducting a meta-analysis
1. Define the Research Question: Clearly articulate the specific
relationship or effect you intend to investigate. This
foundational step guides the entire analysis.
2. Literature Search: Conduct a thorough and systematic search
for relevant studies. Utilize multiple databases and sources
to ensure a comprehensive collection of pertinent literature.
3. Inclusion and Exclusion Criteria: Establish clear criteria to
determine which studies will be included or excluded from
the analysis, ensuring consistency and relevance.
4. Data Extraction: Systematically extract necessary data from
each selected study, focusing on effect sizes, sample sizes,
and other relevant variables.
Hansen, C., Steinmetz, H. & Block, J. How to conduct a
meta-analysis in eight steps: a practical guide. Manag

5. Effect Size Calculation: Compute a standardized measure
of effect size for each study to facilitate comparison and
aggregation.
6. Assess Heterogeneity: Evaluate the degree of variability
among study results to determine if differences are due to
chance or underlying factors.
7. Model Selection and Analysis: Choose an appropriate statistical
model (fixed-effect or random-effects) based on the
heterogeneity assessment and perform the meta-analysis.
8. Interpretation and Reporting: Present the findings, discussing
their implications, potential biases, and limitations.
Transparency in reporting enhances the credibility and utility of
the meta-analysis.
Hansen, C., Steinmetz, H. & Block, J. How to conduct a
meta-analysis in eight steps: a practical guide. Manag

HYPOTHESIS
 “Hypo” Means tentative or subject to verification and
“thesis” means statement about solution of a problem.
 Hypothesis is a formal question that researcher intends to
resolve.
 Hypothesis is predictive statement capable of being tested
by scientific methods that relates an independent variable
to some dependent variable.
 For example students who receive counselling will show a
greater increase in creativity than students not receiving
counselling.

Hypothesis testing
• Aim of doing a study is to check whether the data agree with certain
predictions. These predictions are called hypothesis.
• Significance test- it is a way of statistically testing a hypothesis by
comparing the data values.
• – It consists of two hypothesis-Null(H0) & Alternative hypothesis(H1).
The null hypothesis, H0:
– The hypothesis we wish to falsify
– Assumed to be true until we can prove otherwise.
The alternative hypothesis, Ha:
– The hypothesis we wish to prove to be true
– Hypothesis are formulated before collecting the data.

Types of error
 Type I/ α error- Rejecting true null hypothesis.
– We may conclude that difference is significant, when in
fact there is no real difference.
– It is popularly known as p-value. Maximum p-value
allowed is called as level of significance. Being serious p-
value is kept low, mostly less than 5% or p<0.05.
 Type II/ β error- Accepting false null hypothesis.
– We may conclude that difference is not significant, when
in fact there is real difference.
 – It is also called as Power of the test.
Power of a statistical test is the probability that it
correctly rejects the null hypothesis when the null
hypothesis is false & it indicates sensitivity of the test.

The p-Value
Whether or not we reject the
null is determined by
whether the p-value is below
a certain cut-off, which we
call the alpha value.
Traditionally, we tend to set
alpha at either 0.05 or 0.01.

 For example, if we are testing whether the average
heights of 2 groups of children are different, and perform
a t-test to produce a p-value of 0.02, setting α=0.05,we
can conclude that null hypothesis is rejected and that the
2 groups so indeed have different average heights.
 A useful memory aid:
“If the p is low, the null (hypothesis) must go.”

Test of Significance
 Test of significance is a formal procedure for comparing observed
data with a claim (also called a hypothesis) whose truth we want
to assess.
 Test of significance, infact tells probability of relationship
between 2 variables is just an occurrence by chance.
 Parametric tests used for quantitative tests e.g. Paired Student’s
→
t-test, Unpaired Student’s t-test, ANOVA test (F- test/F-ratio)
 Non parametric tests used for qualitative data e.g. Sign test,
→
Chi square test, Wilcoxan test, Mann Whitney U test (compare
median of two independent samples)

INTERPRETATION AND REPORT
 After collecting and arranging data the researcher has to
accomplish the task of drawing inference followed by
report writing.
 This has to be done very carefully otherwise misleading
conclusions may be drawn and whole purpose of doing
research may get vitiated.
 Thus interpretation and report writing should be done
with utmost care.

INTERPRETATION
 Interpretation refers to the task of drawing inference
from the collected facts after an analytical or an
experimental study
 It is a search for broader meaning of research findings
 The task of interpretation has two major aspects
1. the effort to establish continuity in research
through linking the result of a given study with another
2.the establishment of some explanatory concepts

REPORT WRITING
 Research report is considered a major component of
research study
 Writing of report is the last step in a research study and
requires a set of skills
 This task should be accomplished by the researcher with
utmost care he may seek the assistant and guidance of the
expert for the purpose

Different steps in writing report-
 Logical analysis of the subject matter
 Preparation of the final outline
 Preparation of the rough draft
 Rewriting and polishing
 Preparation of the final bibliography
 Writing of the final draft

CONCLUSION
 Ensures Accuracy & Reliability – A well-defined research methodology
ensures data is collected systematically, leading to valid and reliable
results.
 Guides the Research Process – It provides a structured approach,
helping researchers plan, execute, and analyze their studies effectively.
 Enhances Credibility – A robust methodology increases the study’s
trustworthiness, making findings more acceptable to the scientific
community.
 Facilitates Reproducibility – Clearly outlined methods allow other
researchers to replicate the study, verifying and building upon its
findings.
 Supports Decision-Making – Strong research methods generate high-
quality evidence, aiding policymakers, businesses, and academics in
making informed decisions.

REFERENCES
 Soben peter Essentials of public health dentistry (community
dentistry) 7th edition
 C.R. Kothari research methodology methods and techniques
publishers distributors
 Meta-analysis in medical research Haidich AB Department of
Hygiene and Epidemiology, Aristotle University of Thessaloniki
School of Medicine, Thessaloniki, Greece
 Hansen, C., Steinmetz, H. & Block, J. How to conduct a meta-
analysis in eight steps: a practical guide. Manag Rev Q 72, 1–
19 (2022). https://doi.org/10.1007/s11301-021-00247-4
 Korean J Anesthesiol 2017 December 70(6): 601-605
https://doi.org/10.4097/kjae.2017.70.6.601

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