Study Question: Identify the attributes of a research ...



Identify the attributes of a research study that do and do not directly influence the causal interpretability of the results. Tell two attributes of a study that can make it harder to maintain ongoing equivalence, and so, casual interpretability.

Remember – these are not all great answers! Some are really good and some are just awful. Use both the good one and the bad ones to help you identify the content and structure of a great answer!!

1. The attributes that influence causal interpretability are measurement, assignment, external validity, and internal validity. The interpretability of a study is most effected by external and internal validity, however for a causal relationship to be established, all four must be present. Two attributes that make ongoing equivalence difficult to maintain are the length of time involved in the study and indescrepancies in the procedures used.

2. Some attributes that do affect a studies causal interpretabilty is population, which is initial validity. You want to do random assignment. Two things that would make it hard to maintain ongoing equivalence are if someone drops the study after it has been started, because it messes things up and if someone stops giving answers because they think that there has to be a right and/or wrong.

3. The attributes that do influence the causal interpretability of the results is whether or not the study was a true experiment. The study would have to have random assignment of individuals by the researche before the manipulation of the IV. The researcher would also have to manipulate the IV. The good study would have no confounds and a complete population sampling frame in order to have a good sample. What would not directly influence the causal interpretability is the setting, task, and the population which is part of external validity. What can make the study harder is if it were in a field study, obtaining a complete population sampling frame, and having no confounds. Since this hard to obtain researchers are then forced to have a purposiv sample with potentially no confounds.

4. Two attributes of a research study that influence the causal interpreatability of the results are random assignment and confounding variables.

5. to have causal interpretability you must have a true experiment, with random assignment of individuals by the researcher before manipulation of the IV, and NO CONFOUNDS!

ongoing equivalence is about procedural variables, so anytime there is a difference in procedure between groups that is not the IV,you lose ongoing equivalence. for ex. tests are administered at different times. Also if subjects are allowed to leave before DV is measured, there is a potential for alternate explanations e.g. confounds.

6. Attributes that do contribute to causal interpretablity are design, procedures and assignment. For there to be causal interpretability for must have a true experiment. For this we nee random assignment of the individuals by the researcher before the IV. Then we need the manipulation of the IV and finally we can not have any condfounds. This all deals with internal validty. Things that don't influence causal interpretablity are population, task/stimulus, setting and societal/temporal. All these characteristics of study deal with external validty and they don't influence causal interpretablity.Things that can make it hard to test causal interpretablity is feild study and studies that are longitudinal or take a long time.

7. This colleague thinks that only causal relationships are worth researching. Non-experiments cannot demonstrate causal relationships but they can provide knowledge about associative and attributive relationships. Non-experiments are different from true experiments because either they do not involve random assignment of individuals by the researcher before manipulation of the independent variable, they do not manipulate the independent variable, or they do not involve manipulation of the independent variable before measurement.

8. Causal interpretability is directly influenced by a need for three things: temporal precedence, a demonstratable statistical relationship between the items, and no confounding variables. In addition, the study needs to be a true experiment with random assignment of individuals for causal interpretability. It is hard to maintain ongoing equivalence when procedural variables are not the same for everyone. If people have previous experience with a given condition, the conditions are not the same across the board, or there is more than one differing condition then ongoing equivalence becomes a problem. With this problem, causal interpretability goes out the window. If there are confounds, you cannot causally interpret the data.

9. attributes that do influence causal interpretability are the participant assignment, internal validity, or what group the participants will be in, it must be random assignment by the rearcher before the manipulation of the IV. The second attribute that does influence causal interpretability is the research design, it must be a true experiment. Those that do not affect causal interpretability are the population, the data collection, the setting and the statistical model. Those that we have to worry about are those that are in the field settings and those studies that are longer because these things may affect the ongoing equivalence of the study.

10. Two attributes that make ongoing equivalence harder to maintain is having a long time duratin of the study, like if the study were to take a while to complete. Also poor statistical relatioships will prove to make ongoing equivalence a problem

11. There are a few attributes of a research study that do not directly influence the causal interpretability of the results such as the setting, the participant selection, and the data collection. Attributes that do directly influence the causal interpretability are the manipulation of the IV, and the participant assignment. Two attributes of a study that can make it harder to maintain ongoing equivalence, and so, causal interpretability are the length of the study and something that I think starts with an F but I can't remember.

12. You absolutely must have random assignment of individuals by the researcher before manipulation of the independent variable in order to causally interpret the results of a study. That means that you need a true experiment. However, sampling has no effect on the causality of the research. Because psychologists use the converging operations approach instead of the critical experiment approach, there are over 1000 possible research hypotheses, which makes it harder to maintain causal interpretability. And then, even if you have successfully performed research that agrees with your research hypothesis, converging operations cannot give us "truth." We can never say we have proof, only that we have probabilistic conclusion.

13. There are many attributes that make up a research study. Those that influence causal interpretability are assignment and design. To obtain causal interpretability the study must have random assignment of individuals by the researcher BEFORE manipulation of the independent variable, and it must have manipulation of the independent variable. These two things come from the assingment of the selected sample and the design of the study.

The attributes that do not directly influence causal interpretability include the population, setting, task, data collection, and interpretation. These things mainly affect external validity (generalizability), not causal interpretability which is based on Internal Validity.

Two attributes that make it increasingly difficult to obtain causal interpretability in a study are a field setting, and long-term studies. Each of these attributes detract from the amount of control a researcher has over a study, thus increasing the likelihood of confounds.

14. The attributes of a research study that do directly influence the causal interpretability of the results are assignment and design. To test a causal hypothesis, you must have random assignment of individuals by the researcher before manipulation of the IV, manipulation of the IV, and no confounds. So basically, you need a well run true experiment. The attributes of a research study that do not directly influence the causal interpretability of the results are population, setting, participant sampling, data collection, and statistical models used. The two attributes of a study that can make it harder to maintain ongoing equivalence and causal interpretability are if the study has a field setting and/or if the study is a long-term study.

15. Attributes of a research study that do influence causal interpretability are initial equivalence and external validity, and two that do not are internal validity and ongoing equivalence. Two attributes that could make it harder to maintain ongoing equivalence are: How much experience the counselor has had (in a study related to counseling) and weather or not the participants had the same amount of sessions during the study (also in a study related to counseling).

16. Any aspect of external validity won't directly affect the causal interpretability of a reseach study, but initial and ongoing equivalence play an important role in these studies. Having inconsistent procedures during your study, and anything that you find out about your subjects after the study, will affect the causal interpretability of any study.

17. Attributes that do contribute to causal interpretablity are design, procedures and assignment. For there to be causal interpretability for must have a true experiment. For this we nee random assignment of the individuals by the researcher before the IV. Then we need the manipulation of the IV and finally we can not have any condfounds. This all deals with internal validty. Things that don't influence causal interpretablity are population, task/stimulus, setting and societal/temporal. All these characteristics of study deal with external validty and they don't influence causal interpretablity.Things that can make it hard to test causal interpretablity is feild study and studies that are longitudinal or take a long time.

18. The way the participants are assigned and the design of the study are two things that DO directly influence the causal interpretability of the results. Population, setting, data collection, task/stimulus are some attributes that DO NOT directly influence the causal interpretability of the results. Field settings and longer studies are two attributes that can make it hard to maintain ongoing equivalence.

19. to have causal interpretability you must have a true experiment, with random assignment of individuals by the researcher before manipulation of the IV, and NO CONFOUNDS!

ongoing equivalence is about procedural variables, so anytime there is a difference in procedure between groups that is not the IV,you lose ongoing equivalence. for ex. tests are administered at different times. Also if subjects are allowed to leave before DV is measured, there is a potential for alternate explanations e.g. confounds.

20. The attributes of a study which influence causal interpretability are those which fall under the umbrella of internal validity. That is, initial equivalence: all subject variables must be controlled; there must be random selection of individuals by the researcher before manipulation of the independent variable. Also, ongoing equivalence: all procedural variables must be strictly controlled; there must be no confounds. Attributes which do not directly affect causal interpretability include who the participants of the study are (population), where the study takes place (setting), what the participants do (task/stimulus), and when the study is/was done (temporal). Factors which make it harder to maintain ongoing equivalence are field studies and studies that take place over a long period of time.

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