The most important aspect of this research design is that an evaluator must identify two similar groups, one consisting of individuals who participate in the intervention (treatment group), and the other consisting of those who do not (comparison group). Because in most educational interventions the treatment group is already established, the challenge is to find or create a comparison group. In order to maximize the validity of the comparison, these two groups must be as similar as possible in terms of characteristics prior to the implementation of the intervention. To do this, the evaluator needs data on baseline characteristics of schools, teachers, or students.
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What is a comparison group in education?
Comparison group. The group of students, teachers, or schools that does not participate in the intervention. Variable. Anything that has a quantity or quality that varies and can be measured. Outcome variable. Variable of interest that the intervention is designed to improve, such as teacher evaluation ratings or student test scores.
Can we use comparison groups in qualitative research?
Sally Lindsay, Senior Scientist, Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, and University of Toronto,150 Kilgour Road, Toronto, Ontario, Canada M4G 1R8. Email: [email protected] Qualitative researchers have much to gain by using comparison groups.
How to estimate the treatment group mean from estimated difference?
Since the estimated difference is a weighted average of site specific treatment/ control differences, a logical choice for the estimate of the treatment group mean is to use a similar weighted average of the site treatment group means.
Why is comparability of treatment and control groups important?
The comparability of the treatment and control groups at randomization is also important because it is the first stage in our investigation of a set of methodological problems that could result in biased estimates of channeling's impact.
How do you compare a control group and a treatment?
The treatment group (also called the experimental group) receives the treatment whose effect the researcher is interested in. The control group receives either no treatment, a standard treatment whose effect is already known, or a placebo (a fake treatment).
What makes a good comparison group?
A good comparison group should have substantial overlap with the treatment group in terms of the characteristics likely to affect program outcomes. Informed by the logic model, the evaluator should exercise judgment regarding the key characteristics that should be used to identify similar individuals.
Why do we compare different treatment groups?
Many studies that compare treatments will include a table comparing baseline characteristics between two groups assigned to different treatments. This allows readers to examine if there are any important baseline differences between groups.
What is a comparison group in a research study?
In an experiment testing the effects of a treatment, a comparison group refers to a group of units (e.g., persons, classrooms) that receive either no TREATMENT or an alternative treatment. The purpose of a comparison group is to serve as a source of COUNTERFACTUAL causal inference.
How do you choose a comparison group?
There are two key things that are essential in selecting the comparison group in a cohort study: The unexposed (or less exposed) comparison group should be as similar as possible with respect to other factors that could influence the outcome being studied (possible confounding factors).
Why is it necessary to compare the two groups for this research study?
Comparison groups are important because they help us “control” for any factors that may be influencing the relationship.
How do you compare two treatment groups?
A common way to approach that question is by performing a statistical analysis. The two most widely used statistical techniques for comparing two groups, where the measurements of the groups are normally distributed, are the Independent Group t-test and the Paired t-test.
What is treatment comparison?
Treatment comparison groups are used in studies of treatment effects. Outcomes measured in one group are compared to outcomes in another group. Treatment comparison groups are sometimes categorised as treatment groups (intervention groups or experimental groups) and control groups.
How can you tell if two groups are statistically different?
A t-test is a type of inferential statistic used to determine if there is a significant difference between the means of two groups, which may be related in certain features. The t-test is one of many tests used for the purpose of hypothesis testing in statistics. Calculating a t-test requires three key data values.
Can you compare groups in qualitative research?
Abstract. Qualitative researchers have much to gain by using comparison groups. Although their use within qualitative health research is increasing, the guidelines surrounding them are lacking.
What is a treatment group in statistics?
Treatment groups are the sets of participants in a research study that are exposed to some manipulation or intentional change in the independent variable of interest.
What is the comparison group in an experiment called?
control group, the standard to which comparisons are made in an experiment.
Why is it important to compare like with like?
By ensuring our two groups have similar prognoses (comparing ‘like with like’), we can increase our confidence that any difference we see is due to the treatments and not due to patient differences.
How are participants assigned to groups?
Most commonly, participants are assigned to groups using a computer-generated list of random numbers. Other methods include pre-defined treatment schedules and sealed envelopes with group assignments drawn at random. Again, it is very important that this random allocation occurs before the study starts (prospective allocation) to ensure parallel testing. It is also important that the allocation schedule is concealed.
What happens if a doctor is privy to this allocation scheme and believes the surgery is more effective?
If a doctor is privy to this allocation scheme and believes the surgery is more effective, he may send his sickest patients into one of the lowered numbered rooms instead of a room at random, again increasing the risk in group A.
Why is randomized controlled trial inappropriate?
Though ideal for testing treatments, for some research questions a randomized controlled trial is inappropriate due to ethical or practical concerns. For example, it would be unethical to randomize individuals to a ‘smoking’ vs. ‘no smoking’ group to test whether smoking causes cancer.
What group do high risk patients end up in?
If the severe, high-risk patients are normally situated in low number rooms (closer to the nurses’ station), more severe cases will end up in group A, inflating the risk for the outcome (death) in this group.
How many blogs are there on informed health choices?
This is the fourteenth blog in a series of 36 blogs based on a list of ‘Key Concepts’ developed by an Informed Health Choices project team. Each blog will explain one Key Concept that we need to understand to be able to assess treatment claims.
What do we see at the end of a study?
As real life researchers, all we ‘ see’ at the end of the study are the trial results (ie. more survivors in group A than B). However, if group A fares better than group B, there are actually three possible scenarios:
What is matched-comparison group design?
matched-comparison group design is considered a “rigorous design” that allows evaluators to estimate the size of impact of a new program, initiative, or intervention. With this design, evaluators can answer questions such as:
How is matched-comparison similar to randomized?
Analysis of outcome data for a matched-comparison group design is similar to that for a randomized experiment. In both designs, theoretically the difference in the mean between the treatment and the comparison groups reflects the impact of the intervention. In reality, however, some adjustments are needed. Randomization typically produces two very similar groups, but even so, they are seldom identical. Likewise, matching when done skillfully could produce two very similar groups, but they are never identical. For this reason, the difference in the mean between the two groups is often a bit “off,” and requires some statistical adjustment to arrive at a valid estimate of impact.
Why are comparison groups important?
Comparison groups are important because they help us “control” for any factors that may be influencing the relationship. For instance, you may give students a program and a year later, they’re all doing better, but without a comparison group you won’t know if they would have grown that much with any program or if it was the program you used? Or maybe they all got a lot out of the start of the year seminar and decided to study more? Or maybe they realized college was becoming more expensive and all decided they needed to work harder to get a scholarship? My point is, there are infinite possible explanations for growth with a correlational study. When you add a comparison group, you get to rule a lot of those explanations out.
What are the two major study designs that employ a comparison group?
There are two major study designs that employ a comparison group: experimental and quasi-experimental. Experimental studies are the gold standard. In an experimental study, participants are randomly assigned to either treatment or control, ensuring that confounding factors are also randomly assigned. This is ideal.
When you are evaluating a program’s research base, do you want to ask for data showing both the treatment?
This was a lot of information, but the takeaway is that when you are evaluating a program’s research base, you want to ask for data showing both the treatment and comparison groups . You’ll want to ask what the comparison group was doing instead (nothing? A different program? etc.) and if the groups were initially equivalent. If data meeting these requirements can be provided, the program passes my “comparison group” test.
Why do research based programs still fail kids if they are proven effective?
Why do “research-based” programs still fail kids if they are proven effective? The truth of the matter is that the quality of program evaluation research can vary widely and even if high quality evaluation work is done, the findings from that study may not extend to your students, classroom, or school.
What is the best comparison group for a general cohort study?
As noted earlier, general cohorts employ an internal comparison grou p , e.g., dividing the cohort into quintiles of BMI or quintiles of activity and using the quintile with the lowest BMI or the lowest activity as the reference group. This is the best comparison group for a general cohort study, because the subjects are likely to be similar in some ...
Why is the general population not comparable?
The general population is not really comparable because there are many confounding variables that cannot be controlled for. The general population includes people who are unable to work because of disease or disability (the "healthy worker effect" which is discussed in the module on bias).
What is the challenge of the Air Force Health Study?
The major challenge for the Air Force Health Study (AFHS) and other special cohort studies is selection of an appropriate comparison group. The goal of analytic studies is to compare health outcomes in exposed and unexposed groups that are otherwise as similar as possible, i.e., having the same distributions of all other factors that could have any association with health outcomes. We will see that intervention studies with large numbers of subjects randomly assigned to two or more treatment groups (exposures) can usually achieve this so that the groups being compared have similar distributions of age, sex, smoking, physical activity, etc., but random assignment does not occur in cohort studies. Suppose that a cohort study had smokers who were older than the non-smokers. It is well established that the risk of heart disease increases with age, i.e., it is an independent risk factor for heart disease, and if the smokers are older, they have an additional risk factor that will cause an overestimate of the association between smoking and heart disease. This phenomenon, called confounding, occurs when the exposure groups that are being compared differ in the distribution of other determinants of the outcome of interest. Another concern is that the exposure groups being compared may differ in the quality or accuracy of the data that is being collected, and this can also bias the results (so-called information bias ). Confounding and bias will be discussed later in the course, but for now, it is important to recognize the importance of selecting a comparison group that differs in exposure status but is as similar as possible to the exposed group in all other ways including:
Why are general population data limited to studies of mortality?
General population data are frequently limited to studies of mortality since accurate rates on specific health outcomes may not be available.
When was the study of non-Hodgkin lymphoma?
A study of the association between pesticide exposure and risk of non-Hodgkin lymphoma began in 2011. The incidence of non-Hodgkin's lymphoma was compared in men who worked as pesticide applicators in the 1970s-1980s and men who worked as fertilizer applicators in the 1970s-1980s. Outcome data was collected through 2010.
What is the assumption of repeated measures ANOVA?
So, these two options are too much simple. The Repeated Measures ANOVA has an assumption called "Sphericity", which is rarely met. I suggest you an alternative approach. Use Nested ANOVA, with factors nested in this way: Treatment < Tank < Time.
What to do instead of a student's T test?
Instead of a student's T test, try a paired T-test.''
What is a mixed model ANOVA?
1.Mixed model ANOVA used to assess whether there were significant differences between and within treatments over time.
Is Matheus's ANOVA repeated?
As I understand, the analysis suggested by Matheus is a repeated measures ANOVA on the data in 'long' format. The analysis I proposed is the same, but on the data in 'wide ' format. With only 3 repeated measures, the 'sphericity' issue is not really a huge problem. With most common statistical software packages (SAS, SPSS, R, STRATA) one can model the covariance structure.
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What is an experimental group?
An experimental group is a test sample or the group that receives an experimental procedure. This group is exposed to changes in the independent variable being tested. The values of the independent variable and the impact on the dependent variable are recorded. An experiment may include multiple experimental groups at one time.
What is the difference between experimental and control?
The only difference between the control and experimental group is the independent variable.
What is a control group?
A control group is a group separated from the rest of the experiment such that the independent variable being tested cannot influence the results. This isolates the independent variable's effects on the experiment and can help rule out alternative explanations of the experimental results. While all experiments have an experimental group, ...
What is a placebo in an experiment?
To prevent skewing the results, a placebo may be used. A placebo is a substance that doesn't contain an active therapeutic agent. If a control group takes a placebo, participants don't know whether they are being treated or not, so they have the same expectations as members of the experimental group.
What is controlled experiment?
A simple example of a controlled experiment may be used to determine whether or not plants need to be watered to live. The control group would be plants that are not watered. The experimental group would consist of plants that receive water. A clever scientist would wonder whether too much watering might kill the plants and would set up several experimental groups, each receiving a different amount of water.
What is a positive and negative control?
Positive and negative controls are two other types of control groups: Positive control groups are control groups in which the conditions guarantee a positive result. Positive control groups are effective to show the experiment is functioning as planned. Negative control groups are control groups in which conditions ...
What is a negative control group?
Negative control groups are control groups in which conditions produce a negative outcome. Negative control groups help identify outside influences which may be present that were not unaccounted for, such as contaminants.
