There are two classes of factors that jeopardize the validity of research findings they are internal and external. Internal validity is the extent to which a test measures what it claims to measure. External validity on the other hand, is the extent to which the results of a research study can be generalized to other groups, times, and settings (Trochim and Donnelly, 2008).
Internal validity is threatened whenever there exists the possibility that alternative causes, other than the independent variable, are responsible for the effect. There are a number of possible threats to internal validity, the seven most commonly referenced threats include history, maturation, testing, instrumentation, mortality, regression, and selection. History refers to specific events, in addition to the treatment, that occur between the first and second measurement. The longer the interval between the pretest and posttest, the more viable this threat becomes. Maturation pertains to changes in physical, intellectual, or emotional characteristics, that occur naturally over time, that influence the results of a research study. For example, in longitudinal studies, individuals grow older and become more sophisticated. Testing, refers to the effects of taking a test upon performance on a second testing. Exposure to the pretest may influence performance on a posttest. The shorter the interval between the pretest and posttest, the more viable this threat becomes. Instrumentation is concerned with changes in the way a test or other measuring instrument is calibrated that could account for results of a research study. This threat is most likely to occur from an unreliable measuring instrument (Creswell, 2009).
Mortality refers to the differential loss of indiv...
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...4. Choosing an appropriate research design can help control most other threats to internal validity.
In general, threats to the external validity of a study can be minimized if the researcher has taken steps to insure that the sample, the setting, and the context are representative of the population, setting, and context to which the results are intended to be generalized (Trochim and Donnelly, 2008).
Works Cited
Creswell, J. W. (2009). Research design: Qualitative, quantitative, and mixed methods approaches (3rd ed.). Thousand Oaks, California: SAGE Publications, Inc.
Fraenkel, J. R., & Wallen, N. E. (2006). How to design and evaluate research in education (6th ed.). New York, New York: McGraw-Hill Humanities/Social Sciences/Languages.
Trochim, W. M.K., & Donnelly, J. P. (2008). The research methods knowledge base (3rd ed.). Mason, Ohio: Cengage Learning.
2. The researcher does not want or need to generalize the results to a population.
Internal validity, unlike external and construct validity, deals with causal relationships. In other words, the question is whether any additional research that is found is actually associated with the study that is being conducted. The question, again, is whether we can be confident that the outcome of the study is a result of the experiment itself. What this means is that internal validity is the extent to which a change in a given variable is caused by the change in another variable.
...the data did not involve member checking thus reducing its robustness and enable to exclude researcher’s bias. Although a constant comparative method was evident in the discussion which improved the plausibility of the final findings. Themes identified were well corroborated but not declared was anytime a point of theoretical saturation Thus, the published report was found to be particularly strong in the area of believability and dependability; less strong in the area of transferability; and is weak in the area of credibility and confirmability, although, editorial limitations can be a barrier in providing a detailed account (Craig & Smyth, 2007; Ryan, Coughlan, & Cronin, 2007).
Leedy, P. D., & Ormrod, J. E. (2010). Practical Research Planning and Design (9th ed.). Upper Saddle River, NJ: Pearson Education, Inc.
Salkind, N. J. (2012). 100 questions (and answers) about research methods. Thousand Oaks, CA: SAGE
Replicability and generalizability are important considerations when analyzing research findings. Result replicability measures the extent to which results will remain the same when a new sample is drawn, while generalizability refers to the ability to generalize the results from one study to the population (Guan, Xiang, & Keating, 2004). If results are not replicable they will not be generalizable. Replicability is important because it determines whether results are true or a fluke. Measures of replicability can be obtained using either external or internal methods. External replicability analysis requires redrawing a completely new sample and replicating the study. Internal replicability analysis involves procedures used to investigate replicability within the current study sample (Zientek & Thompson, 2007). Although only external analysis can provide definitive answers regarding result replicability, a flawed assessment of result replicability via internal analysis is still better than conjecture (Thompson, 1994).
The research is not without its limitations. One of the challenges that would be faced would be establishing the accuracy and bias in the various answers given by respondents. Some of the information may be dishonest, biased and unclear. This would render the report unreliable.
However, one can argue that not all research findings are to be believed (Hunt, 1987). A good research should capture the problem and find ways to improve in the setting.
I found it very interesting when talking about experimental research how important validity is. There were two types internal validity and external validity. Internal was more about manipulation/controlling and removing any influence of extraneous variables. By doing so the goal is to be assured that any observed differences between groups in the study is attributed only be differences in the independent variable (e.g., treatment, intervention, and instruction) and no other factors. So, my understanding of this concept is basically understanding and verifying that the research was done right. I was wondering if anyone else got the same conclusion and if there are any other important parts to my understanding of internal validity that I am
Internal validity has two components. First, the estimator of the causal effect must be unbiased and consistent. Second, the standard errors of the estimator must be appropriate to conduct a hypothesis test. Threats to internal validity include omitted variable bias, functional
Creswell, J. W. (2009). Research design: Qualitative, quantitative, and mixed methods approaches (3rd ed.). Thousand Oaks, CA: Sage Publications.
The four different methods of measuring validity are content validity, evidence of validity from contrasting groups, evidence of validity from convergence, and evidence of validity from convergence (Grove et al., 2015, p. 289). Content validity is a measurement of how all the elements of a test are relevant and represent the phenomenon being measured. Evidence of validity from contrasting groups examines how well an instrument correlates in the opposite direction in already established groups (Westen & Rosenthal, 2003). Evidence of validity from convergence measures how the results from a relatively new tool compares in a positive relation to the results from an established tool. Lastly, evidence of validity from divergence measures how the results of a relatively new tool compare in a negative relation to the results of an established tool that measures an opposite phenomenon (Grove et al., 2015, p. 291). Validity of an instrument is paramount in determining how the research relates to the concept that is under
Research findings are considered reliable if they are consistent over a period of time and they accurately represent the total population under evaluation or study (McMillan, 2016; Golafshani, 2013). Moreover, the findings of a research study are considered reliable if they can be reproduced using similar methodology. In this regard, replication and consistency are the two characteristics that determine the reliability of any given research tool or test. Validity establishes if the research study actually measures what it was initially intended to measure (McMillan, 2016). In this regard, validity of a research is determined by how accurate the measurement tool is in measuring what it was intended to establish. Therefore, the quality of research is determined by its reliability and validity. The validity and reliability of any
For example, if we administer a measure of depression to a sample of participants all diagnosed with Major Depressive Disorder, the reliability of those scores does not apply if we administer this instrument to the population at large. For the reliability coefficient to be relevant to a certain population, the population needs to be similar to the sample that was used to assess the reliability initially.
Perri 6 & Christine B., 2012. Principles of Methodology: Research Design in Social Science. London: Sage.