What are the type of study used in the research?

Types of Research

How do we know something exists? There are a numbers of ways of knowing…

  • -Sensory Experience
  • -Agreement with others
  • -Expert Opinion
  • -Logic
  • -Scientific Method (we’re using this one)

The Scientific Process (replicable)

  1. Identify a problem
  2. Clarify the problem
  3. Determine what data would help solve the problem
  4. Organize the data
  5. Interpret the results

General Types of Educational Research

  • Descriptive — survey, historical, content analysis, qualitative (ethnographic, narrative, phenomenological, grounded theory, and case study)
  • Associational — correlational, causal-comparative
  • Intervention — experimental, quasi-experimental, action research (sort of)

What are the type of study used in the research?

Researchers Sometimes Have a Category Called Group Comparison

  • Ex Post Facto (Causal-Comparative): GROUPS ARE ALREADY FORMED
  • Experimental: RANDOM ASSIGNMENT OF INDIVIDUALS
  • Quasi-Experimental: RANDOM ASSIGNMENT OF GROUPS (oversimplified, but fine for now)

General Format of a Research Publication

  • Background of the Problem (ending with a problem statement) — Why is this important to study? What is the problem being investigated?
  • Review of Literature — What do we already know about this problem or situation?
  • Methodology (participants, instruments, procedures) — How was the study conducted? Who were the participants? What data were collected and how?
  • Analysis — What are the results? What did the data indicate?
  • Results — What are the implications of these results? How do they agree or disagree with previous research? What do we still need to learn? What are the limitations of this study?

 

Del Siegle, PhD
[email protected]

Last modified 6/18/2019

Similarly, in the first example, if the researchers found that students with low family income had lower reading scores than students with high family income, they would not be justified in concluding  that low family income causes low reading scores. It might be that the same factors which caused the families to have low or high income (one possibility might be parents' level of education) also influenced the children's reading scores.

Unfortunately, in studying whether family income affects reading scores (and in many other situations), it is not possible to do an experiment -- it is not possible to randomly assign children's families to high or low income. Thus in situations where experiments are not possible, there is more uncertainty in the results. In some such situations, there are methods that can increase our confidence that some causality is taking place.

Note: The meaning of "experiment" used here is a technical one; be sure not to confuse it with other definitions of "experiment." In particular, "experiment" as used in statistics does not mean "try something to see what happens."

II. Classifying according to the purpose of the analysis

In exploratory data analysis, the purpose is to investigate the data to see what patterns can be seen. In confirmatory data analysis, a pattern has been hypothesized before the study, and the purpose of the study is to confirm or disconfirm the hypothesis.

As above, in most cases, an experiment is best for confirmatory data analysis. However, experiments are not always possible. Sometimes all that can be studied is whether the same pattern holds in a new (preferably randomly selected) data set.

Figure 1 shows the tree of possible designs, branching into subgroups of study designs by whether the studies are descriptive or analytic and by whether the analytic studies are experimental or observational. The list is not completely exhaustive but covers most basics designs.

What are the type of study used in the research?

Figure: Tree of different types of studies (Q1, 2, and 3 refer to the three questions below)

> Download a PDF by Jeremy Howick about study designs

Our first distinction is whether the study is analytic or non-analytic. A non-analytic or descriptive study does not try to quantify the relationship but tries to give us a picture of what is happening in a population, e.g., the prevalence, incidence, or experience of a group. Descriptive studies include case reports, case-series, qualitative studies and surveys (cross-sectional) studies, which measure the frequency of several factors, and hence the size of the problem. They may sometimes also include analytic work (comparing factors “” see below).

An analytic study attempts to quantify the relationship between two factors, that is, the effect of an intervention (I) or exposure (E) on an outcome (O). To quantify the effect we will need to know the rate of outcomes in a comparison (C) group as well as the intervention or exposed group. Whether the researcher actively changes a factor or imposes uses an intervention determines whether the study is considered to be observational (passive involvement of researcher), or experimental (active involvement of researcher).

In experimental studies, the researcher manipulates the exposure, that is he or she allocates subjects to the intervention or exposure group. Experimental studies, or randomised controlled trials (RCTs), are similar to experiments in other areas of science. That is, subjects are allocated to two or more groups to receive an intervention or exposure and then followed up under carefully controlled conditions. Such studies controlled trials, particularly if randomised and blinded, have the potential to control for most of the biases that can occur in scientific studies but whether this actually occurs depends on the quality of the study design and implementation.

In analytic observational studies, the researcher simply measures the exposure or treatments of the groups. Analytical observational studies include case””control studies, cohort studies and some population (cross-sectional) studies. These studies all include matched groups of subjects and assess of associations between exposures and outcomes.

Observational studies investigate and record exposures (such as interventions or risk factors) and observe outcomes (such as disease) as they occur. Such studies may be purely descriptive or more analytical.

We should finally note that studies can incorporate several design elements. For example, a the control arm of a randomised trial may also be used as a cohort study; and the baseline measures of a cohort study may be used as a cross-sectional study.

Spotting the study design

The type of study can generally be worked at by looking at three issues (as per the Tree of design in Figure 1):

Q1. What was the aim of the study?

  1. To simply describe a population (PO questions) descriptive
  2. To quantify the relationship between factors (PICO questions) analytic.

Q2. If analytic, was the intervention randomly allocated?

  1. Yes? RCT
  2. No? Observational study

For observational study the main types will then depend on the timing of the measurement of outcome, so our third question is:

Q3. When were the outcomes determined?

  1. Some time after the exposure or intervention? cohort study (‘prospective study’)
  2. At the same time as the exposure or intervention? cross sectional study or survey
  3. Before the exposure was determined? case-control study (‘retrospective study’ based on recall of the exposure)

Advantages and Disadvantages of the Designs

Randomised Controlled Trial

An experimental comparison study in which participants are allocated to treatment/intervention or control/placebo groups using a random mechanism (see randomisation). Best for study the effect of an intervention.

Advantages:

  • unbiased distribution of confounders;
  • blinding more likely;
  • randomisation facilitates statistical analysis.

Disadvantages:

  • expensive: time and money;
  • volunteer bias;
  • ethically problematic at times.

Crossover Design

A controlled trial where each study participant has both therapies, e.g, is randomised to treatment A first, at the crossover point they then start treatment B. Only relevant if the outcome is reversible with time, e.g, symptoms.

Advantages:

  • all subjects serve as own controls and error variance is reduced thus reducing sample size needed;
  • all subjects receive treatment (at least some of the time);
  • statistical tests assuming randomisation can be used;
  • blinding can be maintained.

Disadvantages:

  • all subjects receive placebo or alternative treatment at some point;
  • washout period lengthy or unknown;
  • cannot be used for treatments with permanent effects

Cohort Study

Data are obtained from groups who have been exposed, or not exposed, to the new technology or factor of interest (eg from databases). No allocation of exposure is made by the researcher. Best for study the effect of predictive risk factors on an outcome.

Advantages:

  • ethically safe;
  • subjects can be matched;
  • can establish timing and directionality of events;
  • eligibility criteria and outcome assessments can be standardised;
  • administratively easier and cheaper than RCT.

Disadvantages:

  • controls may be difficult to identify;
  • exposure may be linked to a hidden confounder;
  • blinding is difficult;
  • randomisation not present;
  • for rare disease, large sample sizes or long follow-up necessary.

Case-Control Studies

Patients with a certain outcome or disease and an appropriate group of controls without the outcome or disease are selected (usually with careful consideration of appropriate choice of controls, matching, etc) and then information is obtained on whether the subjects have been exposed to the factor under investigation.

Advantages:

  • quick and cheap;
  • only feasible method for very rare disorders or those with long lag between exposure and outcome;
  • fewer subjects needed than cross-sectional studies.

Disadvantages:

  • reliance on recall or records to determine exposure status;
  • confounders;
  • selection of control groups is difficult;
  • potential bias: recall, selection.

Cross-Sectional Survey

A study that examines the relationship between diseases (or other health-related characteristics) and other variables of interest as they exist in a defined population at one particular time (ie exposure and outcomes are both measured at the same time). Best for quantifying the prevalence of a disease or risk factor, and for quantifying the accuracy of a diagnostic test.

What are the 4 types of research study?

There are four main types of Quantitative research: Descriptive, Correlational, Causal-Comparative/Quasi-Experimental, and Experimental Research.

What are the 5 types of research studies?

Five Basic Types of Research Studies.
Case Studies..
Correlational Studies..
Longitudinal Studies..
Experimental Studies..
Clinical Trial Studies..

What is the most common type of research study?

Explanatory research is the most common type of research method and is responsible for establishing cause-and-effect relationships that allow generalisations to be extended to similar realities.

What are the 7 type of research?

Types of Scientific Research.
Fundamental or Basic research: ... .
Basic research..
Applied research: ... .
Descriptive research. ... .
Explanatory research..
Longitudinal Research. ... .
Cross-sectional Research. ... .
Action research..