Tests of Reliability
Internal consistency
Internal consistency is a reliability test that seeks to ascertain if consistencies exist in parameters that measure a certain construct. The internal consistency reliability test employs multiple experiments or tests and correlates measurements to establish if instruments or the parameters are consistent in measuring the same construct. The test is appropriate when analyzing the effectiveness of parameters or instruments in a given study.
The strengths of internal consistency are that they enhance the accuracy of the results by eliminating possible errors that are inherent in the instrument and reduce the effect of confounding variables in a study. Since instruments have inherent errors that can affect the results, the use of different instruments or carrying out multiple experiments enhances internal consistency and reduces the effect of confounding variables in the study.
The weaknesses of internal consistency are that they reduce the external validity of the findings and it is very expensive to conduct. High internal consistency of the study means that low external validity, which makes it difficult to extrapolate findings to apply in the general populations. Moreover, the use of different instruments and conducting multiple experiments is very expensive.
Split-Half
Split-half is a reliability test that assesses variability of the findings based on two groups of observers or two sets of instruments. The test correlates different findings of the two groups of observers or two sets of instruments to determine their variability and subsequently their reliability in the study. The test is applicable and appropriate in carrying out comparative studies of observations and measurements to establish their reliability in a given study.
The strength of the split-half test is that it eliminates biases due to observation or defect of an instrument. If a group makes a biased observation, the other group acts as a control. Correlation between the two groups results in minimization of the biases inherent in observations. Likewise, the correlation of the instruments minimizes erroneous measurements by the instruments.
The weakness of the split-half test is that the rating of experimental findings using two groups or two sets of instruments is insufficient to warrant their reliability. Another weakness is that two groups of observers or sets of instruments are prone to the effects of confounding variables. Elimination of confounding variables requires the use of varied instruments and diverse observers.
Test-Retest
Test-retest is a reliability test that measures consistency or variability of measurements over a period. The test is applicable and appropriate in carrying out prospective studies that require continued monitoring and assessment at certain intervals of time. The critical factor in the test is consistency or variability of the measurements among various variables of a prospective study.
The strength of the test-retest is that it can measure consistency or variability of measurement over a period thus enhances the reliability of research findings by incorporating the time factor. Moreover, test-retest acts as a confirmation of the research findings as to whether the time factor is a confounding variable or an experimental variable.
The weakness of the test-retest is that it is difficult to calculate the appropriate interval of time that is critical in measuring certain variables without missing significant details of the study because some variables are periodic in their occurrence. Another weakness is that variability can be negligible over a long period or highly variable over a short period, thus unreliable to research.
Parallel and Alternate Forms
Parallel and alternate forms of reliability test assess if different measurements of different instruments have any correlation when measuring the same variable of a study. The test is applicable and appropriate in carrying out comparative studies that seek to establish the reliability of both the instruments and the variables when studying a certain phenomenon.
The strength of the test is that it helps in analyzing the accuracy of the instrument. If the findings of two or more instruments correlate, it means that the instruments are accurate. If there is no correlation, it means that some instruments are either defective or some variables are immeasurable. Furthermore, the test enhances the reliability of the measurements.
The weakness of the parallel and alternate forms of reliability test is that it is hard to establish the existence of confounding variables if all instruments measure similar variables. Also, there is a high probability that one can correlate other variables that have no causal relationship at all as measurements of reliability.
Tests of Validity
Face validity
Face validity is a rational assessment of research design if it measures the required parameters. The validity test is applicable and appropriate in designing research properly by ensuring that essential variables are measurable and rationally have a relationship with the objective of the study. The test helps in the identification of dependent, independent, and confounding variables of research.
Face validity strength is that it prevents unnecessary implementation of a research design that has no rational basis and thus precludes wastage of resources. Moreover, face validity assesses the viability of research design and predicts the validity of research findings in terms of internal and external validity, and therefore important in guiding researchers throughout the research design.
The weakness of the face validity is that it may cause termination of the research design due to poor judgment. Complex research design at times requires practical assessment for one to establish its rationale and viability. Face validity is also inaccurate as it depends on rational ability, which apart from being non-standard is prone to biases.
Content validity
Content validity is a validity test that compares the proposed variables of the research design with actual variables in an experiment to establish whether they tally or they are consistent with the research design. The content validity test is applicable and appropriate when one is set to conduct a study or during the study.
The content validity is important because it ensures that the experimental set up is consistent with the research design. The inconsistencies in the research design and experimental setup degrade the validity of the findings. Besides, it helps the researcher in adhering to the research design while setting up experiments to avoid probable diversion during research.
Content validity test is at times inappropriate in the course of research because researchers have the freedom to modify certain variables of the research design to fit into practical aspects of the study. Furthermore, the content validity test is very restrictive and inflexible to changing parameters that occur in the course of the study.
Criterion Validity
Criterion validity assesses the validity of parameters that measure certain variables in a study. The criterion validity seeks to establish the importance of specific parameters in predicting measurements of variables over a period. The validity test is applicable and appropriate in carrying out prospective studies that require continued monitoring and prediction of outcomes.
The strength of criterion validity is that it assesses the validity of the parameters and variables with a view of eliminating confounding variables that invalidate research findings. Moreover, the criterion validity can effectively predict future outcomes by ensuring that the research findings correlate with standard measurements of other accurate and reliable instruments.
The weakness of the criterion validity is that it is difficult to classify certain variables to fit into a single parameter. Some variables need an assessment on their own rather than in a class of variables because they are subject to confounding variables. Also, it is difficult to correlate the test variable with criterion variables and come up with a conclusive causal relationship.
Construct Validity
Construct validity seeks to establish if there is a rational relationship between theoretical and empirical aspects of an experiment to warrant justification of research findings. For a construct to be valid, there should be a significant correlation between theoretical concepts and empirical findings. Construct validity is the applicable and appropriate invalidation of theories that entail abstract constructs such as creativity and intelligence.
The strength of construct validity is that it determines the correlation between empirical findings and theoretical assumptions, and thus validates the application of theories. Normally, the validation of theories demands that theoretical assumptions must correlate with empirical findings. Construct validity is also very important in the assessment of constructs such as intelligence, emotion, and creativity, which are very abstract.
The weakness of construct validity is that some constructs are very abstract and complex to correlate with empirical findings, and therefore, correlation studies are not reliable in the validation of a theory. Also, construct validity does not sufficiently validate a theory since the validation of theories depends on the empirical rationale.