Measures Of Validity And Reliability

Values and Motives Questionnaire: The Technical Manual (n.d.). Retrieved from the Liberty COUN 521 website: Psytech International.

The Values and Motives Questionnaire, also known as the Values and Motives Inventory, is designed to examine a person’s motivation in relation to his values and activities. In order to ensure a comprehensive understanding of values, the VMQ assess three distinct areas, including: interpersonal, intrinsic, and extrinsic. Interpersonal values, according to the VMQ refer to one’s relationships with others. Intrinsic values contain one’s personal beliefs and attitudes. Finally, extrinsic values are one’s motivating factors at the workplace. Each of these three areas contain twelve topics

In the surveys and randomized controlled trials, validity, reliability and generalizability are three key factors.

Validity refers to the extent to which any piece of information reflects real life as with so many

What is meant by the terms validity and reliability and why are these so important in assessment? Think about the following scenario when preparing your response:

Validity and reliability help ascertain the quality of a piece of research by verifying the trustworthiness of a study. Validity verifies the research is measuring what the researchers intended to study. Validity is measured by degree in particular uses. Researchers must show the inference, to the study, is the proper amount. Validity is commonly examined through evidence based on relations to other variables. This occurs when results from one test are compared to similar tests (McMillan, 2012).

The degree to which a construct is expressed by an individual is assessed through the use of variables. Variables are presented on 5 levels of measurement which are nominal scales, two types of ordinal scales, interval scales, and ratio scales. The variable are organized from least mathematically precise to the most precise. When using a nominal scales numbers are represented as names only, such as gender, blood group or psychiatric disorder. This type of data can only be used for counting. Ordinal scale type I includes data that exist in a rank order , is comparable between various scales and are not comprised of a mathematical system. Examples include horse race results, and US Army rankings. Ordinal scale type II include data that is averaged from an attitude/opinion scale such as movie rankings, grades, and opinion surveys.

Validity and reliability are used to measure whether a study's results are trustworthy or not (Merriam, 1998). Validity includes internal and external validity. Internal validity considers whether researchers really measure what they are purporting to measure and what the findings reflect (Merriam, 1998). Merriam (1998) suggests six ways to increase a study's internal validity: 1) triangulation, 2) member checks, 3) long-term observation, 4) peer examination, 5) participants' involvement, and 6) researcher's bias. This current study employed multiple instruments, such as a survey, interviews, weekly journals, document collection, and field notes, to collect data from the participants and the research site for triangulation.

Discriminant validity can be inferred when the measures of each construct converge on their respective true scores, which are uniquely distinct from those of the others (Churchill. 1979). Discriminant validity was assessed by examining factor correlations and whether the square root of the average variance extracted (AVE) for each construct was larger than its correlation with the other factors. As shown in Table 3, all construct correlations were less

Validity and reliability are two structural fundamental tools in determining the accuracy and purposeful measurement of subject in question. According to Boswell & Cannon 2014, reliability and accuracy are not a determination of validity but are a part of validity’s purposeful measurement. Validity is categorized as logical or statistical and is used to understand or compare subject being measured. For this study, testing was done prior and post simulation and debriefing interventions measuring knowledge and self-confidence of cardiac step-down nurses.

The coefficient reliability analysis revealed that all the scales consisting of more than two items exceeded the recommended Cronbach‟s alpha benchmark of 0.70 (Nunnally, 1978).

The coefficient reliability analysis revealed that all the scales consisting of more than two items exceeded the recommended Cronbach‟s alpha benchmark of 0.70 (Nunnally, 1978).

Confirmatory factor analysis using Maximum Likelihood (ML) estimation was used to examine the hypothesis regarding number of factors their loadings and factor inter correlations. For assessing the model fit the independence model was compared to the hypothesized model. Results revealed that the independence model, which tests the hypothesis that all variables are uncorrelated, was a poor fit for the data and therefore, it should be rejected, χ²(300,N=152)=2814.908,p< 0.005. The literature reveals that ideally, the χ² value should be small and its associated probability value should be greater than

It is important to mention that it was decided to apply a pilot test to 40 customers, with the purpose of measuring the questionnaire’s internal consistency. In the first version, the test was integrated by 22 items distributed in five dimensions and after being undergone to Cronbach’s alpha validity test, the instrument was redesigned to 20 items, as is shown in Graphic 4.

In order to determine the construct validity, factor analysis was carried out with Principal Component Method and Varimax rotation. The purpose of factor analysis was to obtain theoretically meaningful dimensions pertaining to the study.