Validity assessment

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Validity of Experiments
Ransom and Pope did a study in 1992 to assess the relationship between absenteeism from school and respiration brought about by pollution in 1992. Data was collected from both Provo School District and Alpine School District. Absents results were then regressed on the level of contamination, temperature, and other weather conditions. In analyzing the validity of the research, the paper will look into the various types of validity and the different ways through which the text achieves.
Statistical Conclusion Validity can only be achieved if there is a correlation between the treatment and the outcomes. This research delivers it in that the regression results show that there was a definite association between absenteeism and pollution. The analysis of the relationship between pollution and weather data revealed that they have a healthy relationship as the correlation variable was 0.97. Evidence recorded in the paper indicated that high concentration of pollutants affects the quality of air.
Internal Validity, on the other hand, makes inference on the covariance between the presumed treatments and outcomes. As such, it reflects on the causal association of A and B as data is measured. The research paper assumes that increasing concentration of pollutant materials in the air is related to the rise in respiratory systems. The outcome in this assumption is the respiratory systems, and the treatment is particulate pollution (Stern and Elliott 333).

Construct validity is a situation that can only happen if the sample results represent the population. Since the results show that there is a significant relationship between elements of weather such as snowfall and absenteeism, there is a high possibility that the sample represents the population. Since the cause-effect relationship between absence from school and existence of pollution materials in the air holds for both Provo and Alpine District Schools, external validity is explained.
The main threats to validity are the existence of extreme scores, ambiguity about which variables are the causes and what are the effects. Factors such as increased particulate pollutants during winter led to extreme results. The other threat that can be associated with this experiment is the effect of the setting. For instance, when it was done in the cold season, the results were negatively affected. Although the study aimed at evaluating school absenteeism as a morbidity indicator, other factors may make students not report to a school other than illnesses. This type of threat is known as experimental bias. Lack of causal relationship between the variables in such a case may be a threat towards the achievement of validity (Stern and Elliott 67).
Adequate sampling, use of appropriate statistical measures such as mean, mode, and median and reliable tools can help in achieving Statistical, Conclusion Validity. Repetition of the experiment many times improves validity because similar data is collected and results are observed over time through the use of particular methodology. Therefore, repeating will lead to a rise in the sample size. The other way through which validity can be improved is through control. The measured variables such as time, temperature and age should be maintained for production of valid data. This will ensure that introduction of errors is controlled.
The use of qualitative research design in the experiment improved its validity through repetition. The research process was done in two schools and repeated in tree sites. The monitoring process in Utah valley was done according to the set EPA guidelines. The use of regression method of analysis in the experiment helped in determining how the variables related to each other thereby achieving proved validity.
Work cited
Stern, G., and R. S. Elliott. “Resonant length of longitudinal slots and validity of circuit representation: Theory and experiment.” IEEE Transactions on Antennas and Propagation 33.11 (1985): 1264-1271.