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Assignment: Discriminate Quasi Experimental Research Paper Assignment: Discriminate Quasi Experimental Research Paper Assignment: Discriminate Quasi Experimental Research Paper Description You have been asked to help budding researchers understand the difference between quasi-experiments and true experiments. Prepare a tip sheet that could be shared with others that may also serve as a helpful tool for you as you continue your studies. You may include graphics, tables, or other visuals to support your work. To begin, provide an example of a quasi-experimental research design where you are studying differences among individuals within pre-existing groups or conditions that occur naturally within the real world. Briefly describe the study, and then include the following in your tip sheet: Explain the issue of random assignment, and detail why it would be necessary to conduct a quasi-experimental study and not a true experiment in this hypothetical study. Interpret how this group membership could be impactful in understanding the results. Conclude with a brief exploration of what you would need to do to convert this into a true experiment, theoretically speaking. A quasi-experiment is an empirical interventional study used to estimate the causal impact of an intervention on target population Assignment Discriminate Quasi Experimental Research Paper without random assignment. Quasi-experimental research shares similarities with the traditional experimental design or randomized controlled trial, but it specifically lacks the element of random assignment to treatment or control. Instead, quasi-experimental designs typically allow the researcher to control the assignment to the treatment condition, but using some criterion other than random assignment (e.g., an eligibility cutoff mark).[1] Click here to ORDER an A++ paper from our Verified MASTERS and DOCTORATE WRITERS: Assignment: Discriminate Quasi Experimental Research Paper Quasi-experiments are subject to concerns regarding internal validity, because the treatment and control groups may not be comparable at baseline. In other words, it may not be possible to convincingly demonstrate a causal link between the treatment condition and observed outcomes. This is particularly true if there are confounding variables that cannot be controlled or accounted for.[2] With random assignment, study participants have the same chance of being assigned to the intervention group or the comparison group. As a result, differences between groups on both observed and unobserved characteristics would be due to chance, rather than to a systematic factor related to treatment (e.g., illness severity). Randomization itself does not guarantee that groups will be equivalent at baseline. Any change in characteristics post-intervention is likely attributable to the intervention. The first part of creating a quasi-experimental design is to identify the variables. The quasi-independent variable will be the x-variable, the variable that is manipulated in order to affect a dependent variable. “X” is generally a grouping variable with different levels. Grouping means two or more groups, such as two groups receiving alternative treatments, or a treatment group and a no-treatment group (which may be given a placebo – placebos are more frequently used in medical or physiological experiments). The predicted outcome is the dependent variable, which is the y-variable. In a time series analysis, the dependent variable is observed over time for any changes that may take place. Once the variables have been identified and defined, a procedure should then be implemented and group differences should be examined.[3] Order Now