314512 Lecture Notes - Lecture 3: Null Hypothesis, Cohort Analysis, Cohort Study
P. I. C. O → elements of a hypothesis and null hypothesis
- Population (P)
- Intervention (Independent variable) (I)
- Comparison (Control Group) (C)
- Outcome (Dependent variable) (O)
Null hypothesis outline:
The (I) in (P) does not improve the (O) compared to the (C).
Alternate hypothesis outline:
The (I) in (P) does improve the (O) compared to the (C).
Qualitative Research Design
Primary exploratory research. Used to gain an understanding of underlying reasons, opinions and
motivations
Quantitative Research Design
More logical and data-led approach which provides a measure of what people thnk from a statistical
and numerical point of view.
Correlation coefficient
‘epeseted as . It is a ue etee +1 ad -1 that is calculated to illustrate the relationship
between two variables or sets of data.
- Correlation is positive when the values increase together.
- Correlation is negative when on value decreases and the other increases.
Independent varible → x-axis
Dependant variable → y-axis
Definitions:
Hypothesis (alternate)→ proposed explanation made on the
basis of limited evidence as a starting point.
Null hypothesis → the opposite of a hypothesis with the word
o, ot o oe i it.
Week 3: Research designs
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- +1 is a perfect positive correlation
- 0 is no correlation
- 1 is a perfect negative correlation
Types of research designs
1. General Structure and Writing Style
The function of a research design is to ensure that the evidence obtained enables you to effectively
address the research problem logically and as unambiguously as possible. In social sciences research,
obtaining information relevant to the research problem generally entails specifying the type of
evidence needed to test a theory, to evaluate a program, or to accurately describe and assess meaning
related to an observable phenomenon.
With this in mind, a common mistake made by researchers is that they begin their investigations far
too early, before they have thought critically about what information is required to address the
research problem. Without attending to these design issues beforehand, the overall research problem
will not be adequately addressed and any conclusions drawn will run the risk of being weak and
unconvincing. As a consequence, the overall validity of the study will be undermined.
The length and complexity of describing research designs in your paper can vary considerably, but
any well-developed design will achieve the following:
1. Identify the research problem clearly and justify its selection, particularly in relation to any
valid alternative designs that could have been used,
2. Review and synthesize previously published literature associated with the research problem,
3. Clearly and explicitly specify hypotheses [i.e., research questions] central to the problem,
4. Effectively describe the data which will be necessary for an adequate testing of the
hypotheses and explain how such data will be obtained, and
5. Describe the methods of analysis to be applied to the data in determining whether or not the
hypotheses are true or false.
The organization and structure of the section of your paper devoted to describing the research
design will vary depending on the type of design you are using. However, you can get a sense of what
to do by reviewing the literature of studies that have utilized the same research design. This can
provide an outline to follow for your own paper.
2. Case Study Design
Definition and Purpose
A case study is an in-depth study of a particular research problem rather than a sweeping statistical
survey or comprehensive comparative inquiry. It is often used to narrow down a very broad field of
research into one or a few easily researchable examples. The case study research design is also useful
for testing whether a specific theory and model actually applies to phenomena in the real world. It is
a useful design when not much is known about an issue or phenomenon.
What do these studies tell you?
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1. Approach excels at bringing us to an understanding of a complex issue through detailed
contextual analysis of a limited number of events or conditions and their relationships.
2. A researcher using a case study design can apply a variety of methodologies and rely on a
variety of sources to investigate a research problem.
3. Design can extend experience or add strength to what is already known through previous
research.
4. The design can provide detailed descriptions of specific and rare cases.
What these studies don't tell you?
1. A single/small number of cases offers little basis for establishing reliability or to generalize the
findings to a wider population of people, places, or things.
2. Intense exposure to the study of a case may bias a researcher's interpretation of the findings.
3. Design does not facilitate assessment of cause and effect relationships.
4. Vital information may be missing, making the case hard to interpret.
5. The case may not be representative or typical of the larger problem being investigated.
6. If the criteria for selecting a case is because it represents a very unusual or unique
phenomenon or problem for study, then your intepretation of the findings can only apply to
that particular case.
3. Cohort Design
Definition and Purpose
Often used in the medical sciences, but also found in the applied social sciences, a cohort study
generally refers to a study conducted over a period of time involving members of a population which
the subject or representative member comes from, and who are united by some commonality or
similarity. Using a quantitative framework, a cohort study makes note of statistical occurrence within
a specialized subgroup, united by same or similar characteristics that are relevant to the research
problem being investigated, rather than studying statistical occurrence within the general population.
Using a qualitative framework, cohort studies generally gather data using methods of observation.
Cohorts can be either "open" or "closed."
• Open Cohort Studies [dynamic populations, such as the population of Los Angeles] involve a
population that is defined just by the state of being a part of the study in question (and being
monitored for the outcome). Date of entry and exit from the study is individually defined,
therefore, the size of the study population is not constant. In open cohort studies, researchers
can only calculate rate based data, such as, incidence rates and variants thereof.
• Closed Cohort Studies [static populations, such as patients entered into a clinical trial] involve
participants who enter into the study at one defining point in time and where it is presumed
that no new participants can enter the cohort. Given this, the number of study participants
remains constant (or can only decrease).
What do these studies tell you?
1. The use of cohorts is often mandatory because a randomized control study may be unethical.
For example, you cannot deliberately expose people to asbestos, you can only study its effects
on those who have already been exposed. Research that measures risk factors often relies
upon cohort designs.
2. Because cohort studies measure potential causes before the outcome has occurred, they can
deostate that these auses peeded the outoe, theey aoidig the deate as to
which is the cause and which is the effect.
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Document Summary
Week 3: research designs: i. c. o elements of a hypothesis and null hypothesis. Hypothesis (alternate) proposed explanation made on the basis of limited evidence as a starting point. Null hypothesis the opposite of a hypothesis with the word (cid:858)(cid:374)o(cid:859), (cid:858)(cid:374)ot(cid:859) o(cid:396) (cid:858)(cid:374)o(cid:374)e(cid:859) i(cid:374) it. The (i) in (p) does not improve the (o) compared to the (c). The (i) in (p) does improve the (o) compared to the (c). Used to gain an understanding of underlying reasons, opinions and motivations. More logical and data-led approach which provides a measure of what people thnk from a statistical and numerical point of view. It is a (cid:374)u(cid:373)(cid:271)e(cid:396) (cid:271)et(cid:449)ee(cid:374) +1 a(cid:374)d -1 that is calculated to illustrate the relationship between two variables or sets of data. Correlation is positive when the values increase together. Correlation is negative when on value decreases and the other increases. Types of research designs: general structure and writing style.
