Research Methods
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25 terms
Terms | Definitions |
|---|---|
 Validity | The quality of supporting the intended point of claim; soundness or cogency. |
| Statistical Conclusion Validity | The appropriate use of statistics to infer whether the presumed independent and dependent variables co-vary |
| Internal Validity | the validity of causal inferences in scientific study, usually based on experiments as experimental validity. Researchers results are basically judged in internal validity. |
| Construct Validity | Whether a scale measures or correlates with the theorized psychological scientific construct. Are you measuring what you think you're measuring. |
| External Validity | The validity of causal inferences in scientific studies it's whether the results in the general population can be applied in real world circumstances. |
| Reliability | the degree to which a procedure measures what it claims to measure |
| Internal consistency Reliability | defines the consistency of the results delivered in a test, ensuring that the various items measuring the different constructs deliver consistent scores. |
| Test-Retest Reliability | Variation in measurements taken by a single person or an item under the same conditions. If you retest someone after a period of time. and the results are similar you have high TRTR. Results can change tho as people do change. |
| Concurrent Validity | Validating a scale against something in the outside world. Give your scale to 2+ groups and see if the scale differentiates them as you expected. |
| Convergent Validity | How well does your scale correlate with other constructs you expect it to correlate with and does not correlate with. The degree to which your scale is or isn't similar to other operations. |
| Face Validity | Are you questions measuring the construct in question. Does it look like its going to measure what you want it too |
| Predictive Validity | The extent to which a score on a scale or test predicts scores on some criterion measure. Important when predicting some real world outcome. |
| Factorial Experiment | an experimental design consisting of two or more factors. I.E Control, low drug, med drug and high drug. |
| Repeated Measures Experiment | The repeated measures design uses the same subjects with every condition of the research, including the control. |
| Repeated Measures advantages | Experiment is more efficient and keep variability low. Validity of results are higher while still allowing for a smaller than usual subject groups |
| Repeated Measures disadvantages | May not be possible for each subject to sit in each group. Threats to internal validity (scores regress towards means, subjects may change) These are called regression and maturation threats. |
| Single-Subject Design | subject serves as his own control. Rather than comparing a group of subjects SSE relies on comparing treatment effects on a single subject. |
| Advantages of Experimental Methods | If the controlled experiment goes to plan and gets a positive result our research question is instantly backed. |
| Disadvantages of EM | Sometimes unethical. It would be a challenge to force someone to or not do do some things. |
| Correlation design | get a group of people and measure them on two different things and see if they correlate. |
| Correlation Advantages | Easy and cheap to do. You don't have any scale issues. You're measuring the real life effects. |
| Correlation Disadvantages | Finding a positive correlation does not necessarily mean causation. There could be a third variable. |
| Quasi Experiment | Tend to be used opportunistically. The govt often uses them naturally controlled/ something other than the experimenter is manipulating the variable. They evaluate effects of changes in the real world. |
| QE Advantages | Real world. Practical. Answers the real-world questions we want answered. |
| QE Disadvantages | Measuring is harder in QE. Timing of IV in Quasi experiments are more uncertain. |
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