Methadology

Where are we know …….

Chapter 1 Chapter Chapter
2 3

Research Design
& Sampling

Hamidah Ishak
KSKB JB

Chapter 3 : Methodology

3.1 Design of the study
3.2 Population and sampling
3.3 Research instrumentation
3.4 Data collection procedures
3.5 Proposed framework for data analysis
3.6 Ethical consideration
3.7 Limitations of the study

Research
Design

Introduction

Research design is the plan,structure and strategy of
investigation of answering the research question is
the overall plan ,the researcher select to carry out
their study

Purpose of Research Design

— Actual plan for collection and analysis data.

— Encompasses the methodology and procedures employed to
conduct scientific research.

— It is plan or strategy specifying the procedure to test the study

hypothesis or seeking answer to the research question.

— To provide the scheme for answering the specific research
questions.

Research Design Experimental

Research Non
Design experimental

Experimental research/design

— Scientifically sophisticated research method

— Defined as observation under controlled condition

— It studies observables changes that take place in
order to establish a cause and effect relationship.

Characteristic The researcher the
1. Manipulation independent variable(the
researcher actively applied
2. Control
3.Randomization the treatment to the
participant

The researcher has
controlled over assignment

of group to treatment

The researcher randomly
assign participant to group

Type a.True Experimental
Design
Main
experimental b.Quasi-Expiremental
research Design Design

c.Non –Experimental
Design

a.True - experiment design

— Studies the relationship between dependent &
independent variable.

— Manipulate the independent variable & observe
the changes in dependent variable.

— Used in when respondent are randomly assigned to
equivalent groups(treatment & control group).

5 true experimental research design Post test design

True Pre-test and post
Experimental test design

design solomon four
group design

Treatment
replacement

design

factorial design

1.Post- test Design

— It has higher rate of internal validity
— Respondant are randomly distributed into 2 group
— The dependent variable will only be measured once

throughout the post test
— Pre test are not required as both respondent are

considered to have same characteristic
— 2 post - test design :

◦ Comparative design – comparison between the control and
treatment group

◦ Relative Comparison design – comparison among
treatment group

2.Pre-Test and Post-Test Design

— The dependent variable is measured twice (before
and after the independent variable is manipulated)
in order to find out how much it was affected by the
manipulated variable .

3.Solomon Four-Group Design

— Research respondent being tested more than once.

— Responses given by respondents in the second
test(post-test) are influenced by the first test(pre-
test).

— 2 group of respondent who are given treatment and
2 groups of respondent who are not given
treatment.

— 2 groups of respondent who are given the pretest
and 2 groups of respondent who are not given the
pre-test.

4.Treatment Replacement Design

— Suitable for identifying testing effects in a research
that aims to study the effectiveness of a programme
in institution.

— 3 measurement in two different phase are
conducted on each of the group of respondent.

5.Factorial Design

— Researcher want to find out wheter there are more
than one factor that influence the cause –effect
relationship in a research.

— The design with more than one independent
variable(or factor) is called the factorial design.

b.Quasi-Experimental Research

— Design studies the relationship between dependent and
independent variables

— Priorities the natural difference between group of
respondent

— Used when respondent cannot be randomly assigned
into equivalent groups (Treatment & controlled group)

— Used to evaluate the effectivenes of a programme
where respondent cannot be randomly
assigned,meaning that both respondent group are not
equal balanced or similar characteristic.

3 quasi- Nonequivalent
experimental Group Pretest and

post test design

Regression
discontinuity

design

Time series
Design

1.Non equivalent group

— 2 groups of respondent (treatment group & control
group),and group are measured twice (pretest and
post test) to determine the effectivenes of treatment.

— Can analyse use SPANOVA(split Plot ANOVA).

2.Regression Discontuinity Design

— Can be used to gauge the effectiveness of a remedial
programmes in a organisasion.

— Selection of treatment and control groups based on
a cut off point.

— The researcher only administer treatment to groups
that really required.

— Design has higher validity

3 .Time series Design

— The same measurement to be taken repeatedly on
the dependent variable at the different time before
and after treatment is given

— Required much time and energy

c.Non-experimental Design

— When treatment cannot be implement because the
independent variable (gender,age & race)exist
naturally.

— To study the relationship between the independent
and dependent variables without manipulating the
independent variable .

Types of non-experimental designs

a) Descriptive design
b) Exploratory designs
c) Co-relational research designs
d) Retrospective designs

a.Descriptive design

— information is collected without changing the
environment (i.e., nothing is manipulated).

— provide information about the

◦ naturally occurring health status
◦ Behavior
◦ attitudes
◦ other characteristics of a particular group

b.Cross sectional study design

— It involves collection of data at one point in time (data
from the same person only once, or data from the same
community only once)

— appropriate for describing the status of phenomena or
relationships among phenomena at a fixed point

— involve data collection from a population at one
specific point in time. The aim is to provide data on the
entire population under study

— descriptive study (neither longitudinal studies nor
experimental).

— They can be used to describe odds ratio, absolute risk
and relative risk from prevalence

c.Longitudinal study design

— involves collection of data at different points in
time over an extended period in order to study
changes.

— This method is typically expensive, time
consuming, and subject to the risk of attrition

— refer to panel study or cohort study used to
analysis of risk factor and follow a group of people
who do not have the disease and used correlations
to determine the absolute risk of subject contraction



d.Observation study design

— Descriptive studies, in which the researcher
interacts with the participant, may involve surveys
or interviews to collect the necessary information.

e.Retrospective study design

— Descriptive studies in which the researcher does not
interact with the participant include observational
studies of people in an environment (e.g., "fly on the
wall") and studies involving data collection using
existing records (e.g., medical record review).

f.Cohort study of Panel study design

§A cohort is a group of people who share of
common characteristic or experience to within
a defined period

§ It refers to the same people in the study that
provide data at two or more points in time

g.Exploratory design

— is defined as the initial research into a hypothetical
or theoretical idea. This is where a researcher has
an idea or has observed something and seeks to
understand more about it.

— research project is an attempt to lay the
groundwork that will lead to future studies or to
determine if what is being observed might be
explained by a currently existing theory.

— Most often, exploratory research lays the initial
groundwork for future research

f.Analytic design

STUDY TYPE

Study Types Quantitative
Qualitative

Quantitative Research

Is a formal, objective, systematic process in
which numerical data are used to interpret
result

a. Descriptive design
use if you want to evaluate or explain/audit a
problem

b. Exploratory design
The focus is on gaining insights and familiarity for
later investigation or undertaken when problems
are in a preliminary stage of investigation

c. Co – relational research designs
A correlation is simply defined as a relationship
between two variables. The whole purpose of
using correlations in research is to figure out
which variables are connected

d. Retrospective design

◦ if you collect data from available records

Characteristics

— The data is usually gathered using structured
research instruments.

— The results are based on larger sample sizes that
are representative of the population.

— The research study can usually be replicated or
repeated, given its high reliability.

— Researcher has a clearly defined research question
to which objective answers are sought.

Characteristics

— All aspects of the study are carefully designed
before data is collected.

— Data are in the form of numbers and statistics,
often arranged in tables, charts, figures, or other
non-textual forms.

— Project can be used to generalize concepts more
widely, predict future results, or investigate causal
relationships.

— Researcher uses tools, such as questionnaires or
computer software, to collect numerical data

specific strengths

— Allows for a broader study, involving a greater
number of subjects, and enhancing the generalization
of the results;

— Allows for greater objectivity and accuracy of results.
Generally, quantitative methods are designed to
provide summaries of data that support generalizations
about the phenomenon under study. In order to
accomplish this, quantitative research usually involves
few variables and many cases, and employs prescribed
procedures to ensure validity and reliability;

specific strengths

— Applying well-established standards means that the
research can be replicated, and then analyzed and
compared with similar studies;

— You can summarize vast sources of information and
make comparisons across categories and over time;
and,

— Personal bias can be avoided by keeping a 'distance'
from participating subjects and using
accepted computational techniques.

Specific limitations

— Quantitative data is more efficient and able to test
hypotheses, but may miss contextual detail;

— Uses a static and rigid approach and so employs an
inflexible process of discovery;

— The development of standard questions by researchers
can lead to "structural bias" and false representation,
where the data actually reflects the view of the
researcher instead of the participating subject;

— Results provide less detail on behavior, attitudes, and
motivation;

— Researcher may collect a much narrower and
sometimes superficial dataset;

Specific limitations

— Results are limited as they provide numerical descriptions
rather than detailed narrative and generally provide less
elaborate accounts of human perception;

— The research is often carried out in an unnatural, artificial
environment so that a level of control can be applied to
the exercise. This level of control might not normally be in
place in the real world thus yielding "laboratory results"
as opposed to "real world results"; and,

— Preset answers will not necessarily reflect how people
really feel about a subject and, in some cases, might just
be the closest match to the preconceived hypothesis.

Things to keep in mind when reporting the results of a
study using quantiative methods

— Things to keep in mind when reporting the results of a study
using quantiative methods:

— Explain the data collected and their statistical treatment as well as
all relevant results in relation to the research problem you are
investigating. Interpretation of results is not appropriate in this
section.

— Report unanticipated events that occurred during your data
collection. Explain how the actual analysis differs from the planned
analysis. Explain your handling of missing data and why any
missing data does not undermine the validity of your analysis.

— Explain the techniques you used to "clean" your data set.
— Choose a minimally sufficient statistical procedure; provide a

rationale for its use and a reference for it. Specify any computer
programs used.

Things to keep in mind when reporting the results of a
study using quantiative methods

— Describe the assumptions for each procedure and the steps
you took to ensure that they were not violated.

— When using inferential statistics, provide the descriptive
statistics, confidence intervals, and sample sizes for each
variable as well as the value of the test statistic, its direction,
the degrees of freedom, and the significance level [report the
actual p value].

— Avoid inferring causality, particularly in nonrandomized
designs or without further experimentation.

— Use tables to provide exact values; use figures to convey
global effects. Keep figures small in size; include graphic
representations of confidence intervals whenever possible.

— Always tell the reader what to look for in tables and figures.

Qualitative research

— for investigative methodologies, describe as
ethnography, naturalistic inquiry, anthropological,
field or participant observer research

— involves the investigation of phenomena, typically in
an in-depth and holistic fashion, through the
collection of rich narrative materials using a flexible
research design

— concerns of feelings and is descriptive in nature.

— seeks to understand human and social behavior from
insider’s perspective in a social setting

Characteristic

The Design
— Naturalistic :refers to studying real-world situations

as they unfold naturally; nonmanipulative and
noncontrolling; the researcher is open to
whatever emerges [i.e., there is a lack of
predetermined constraints on findings].

— Emergent : acceptance of adapting inquiry as
understanding deepens and/or situations change;
the researcher avoids rigid designs that eliminate
responding to opportunities to pursue new paths of
discovery as they emerge.

— Purposeful : cases for study [e.g., people,
organizations, communities, cultures, events, critical
incidences] are selected because they are
“information rich” and illuminative. That is, they offer
useful manifestations of the phenomenon of interest;
sampling is aimed at insight about the phenomenon,
not empirical generalization derived from a sample
and applied to a population.

Advantage

— generate rich, detailed data that leave the
participants' perspectives intact and provide
multiple contexts for understanding the
phenomenon under study.

— qualitative research can be used to vividly
demonstrate phenomena or to conduct cross-
case comparisons and analysis of individuals or
groups