Validity in Quantitative Research Designs


Importance of Statistical Conclusion Validity

It utilizes null hypothesis significance testing (NHST) to show therelationships between two variables (dependent and independent) inthe population, based on the study area. The actions in the NHSTinclude the statement of both null and alternative hypotheses,decisions on criteria for statistical essence, choice of test data,determination of information quantity, statistics collection, entryof figures in computer files, debugging, computation of primarydescriptive statistics related to the resultant effect, computing thetest data value, comparison of value to criteria significance, aswell as computation of effect estimates’ strengths. Foreffectiveness in the use of statistical conclusion validity, it isvital to reduce entities that could cause Type I or Type II errors,since it impossible to eliminate them entirely this implies thatperfect validity is non-existent (Portney&amp Watkins, 2015). Apparently, it is the most essential ofthe four classes of validity. Not only can it be used in quantitativeresearch, but also in qualitative studies.

Importance of Internal Validity

Generally, internal validity helps to validate conclusions inquantitative studies, based on their accurate reflection of the topicunder examination. In this respect, this validity primarily focuseson cause and effect relationship in a given study. It ensures a goodrelationship between dependent and independent variables (Portney&amp Watkins, 2015). Nonetheless, it is worth noting thatcorrelation does not guarantee causation. For instance, in a researchinvolving smoking and incomes levels, it is possible to discover arelationship between low-income and smoking habits however, onecannot confirm whether or not one aspect causes the other. It is ofconcern to note that this validity does not dwell on the expectedresults or the possibility of generalizations in a given study. In abid to enhance internal validity, temporal precedence is utilized toestablish the strength of cause and effect associations.

Importance of Construct Validity

Primarily, construct validity aids to determine the extent to whichinferences can be made from different operations in a given researchto the theoretical dimensions that influence the utilized operations.It determines the adequate representation of operational variables intheoretical constructs (Gerhart,2012). In a way, it aids a researcher to categorize researchelements into theoretical and observable entities. Theoreticalentities are formulated in an individual’s mind to enhance ease inexplaining or articulating essential concepts of a research toothers. Typically, it encompasses ideas, hypotheses, hunches, andtheories that one possesses on the world. In most cases, researchersderive concepts they attempt to effect from this theoreticalperspective. On the other hand, the observable dimension consists ofactual treatment, measures, and procedures of observation in relationto a given research. Notably, products of this dimension are derivedfrom imaginations in the theoretical viewpoint. For this reason,construct validity determines how accurate or consistent theresearchers’ ideas and theories are reflected in the actual work.

Importance of External Validity

The validity determines the ability of causal relationships to begeneralized to varied measures, settings, times, and people.Essentially, external validity can be viewed as the ultimate assessorof a research’s suitability. A research work that has insufficientinformation to be translated into practice is considered ineffective.In this regard, the validity is critical in decision-making by keystakeholders in the nursing sector (Peters,Langbein, &amp Roberts, 2015). For instance, insights offailure from previous studies are vital in improving future nursingresearch. It is crucial to note that external validity is achievedthrough generalizations or laboratory procedures from samples.


Gerhart, B. (2012). Constructvalidity, causality, and policy recommendations: The case of highperformance work practices systems. HumanResource Management Review,&nbsp22(2),157-160.

Peters, J., Langbein, J., &ampRoberts, G. (2015).&nbspThere’sNo Escape from External Validity–Reporting Habits of RandomizedControlled Trials.Working Paper.

Portney, L. G., &amp Watkins, M.P. (2015).&nbspFoundationsof clinical research: applications to practice.FA Davis.