On the other hand, measurement is also known as a procedure for assigning symbols, letters, or numbers to empirical properties of variables. This magnitude is represented by a unit of measurement, such as a meter, Celsius or a kilogram. Validity refers to the accuracy of a measure (whether the results really do represent what they are supposed to measure).Reliability and validity are key concepts in the field of psychometrics, which is the study of theories and techniques involved in psychological measurement.Common definition for measurement is the process of determining the magnitude of a quantity, for example length, temperature, or mass. Reliability and validity are both about how well a method measures something: Reliability refers to the consistency of a measure (whether the results can be reproduced under the same conditions).It is also known as external validity. Validity refers to whether the study or measuring test is measuring what is claims to measure.Generalisability is the extent to which the findings of a study can be applicable to other settings. For example, if a research study takes place, the results should be almost replicated if the study is replicated. His theory in an article named “On the theory of scales of measurement”, Stevens proposed that scientifically, all measurement can be classified into four different types of scales namely “nominal”, “ordinal”, “interval” and “ratio”.External reliability refers to how consistent the results are when the same procedures are carried out for a test. The “levels of measurement”, or also known as scales of measure are the term that normally refer to the theory of scale which was founded and developed by the psychologist Stanley Smith Stevens in 1946.
He had invented three famous different methods known as the method of equal-appearing intervals, successive intervals, and the paired comparisons. Besides being one of the first, Thurstone was the most renowned productive scaling theorist. It is equal-appearing intervals constructed from a big pool of statements or issues regarding an attitude that are ranging from strongly negative via neutral to strongly positive. However, Thurstone scale of attitude measurement is normally be used with empirical behaviors of agree-disagree responses. Validity And Reliability Psychology Series Of ItemsThe Guttman scale applies to series of items that have binary results such as an achievement test. Their agreements with one particular item will also agree with lower rank-order items of that particular item. These respondents will mark the items that they agree, which later the set of the responses will be arranged into a hierarchy. This method analyses a large pool of attitudes statements object that are administered by a group of respondents. This hierarchy of an item measured normally implies the probable agreement with items below it and is constructed with the scalogram analysis method. Guttman scale emphasis on the hierarchical order of the items measured. Actually, it is popularly used scale in questionnaires and in survey research. This technique portrays a set of attitude statements or issues. It was first introduced to measure attitudes and was termed as “A technique for the Measurement of Attitudes”. These properties determine which statistical analysis would be used (). As a result, level of measurement describes the relationship among these four values can be depicted as in figure 1 below:Figure 1, relationship among variable, attributes andvaluesIn statistic, scales of measurement refer to ways in which variables/numbers are defined and categorized with certain properties. For the purpose of analyzing the outcome of this variable, we then assign those attributes with the numerical value of 1, 2, 3, and 4. For instance, let assumes school association as the variable and the attributes for this variable are English, Mathematics, Physics, and Geography association. These values that representing those attributes are normally been assigned with number. Zte cell phones for saleFor this reason nominal scale has been known as a categorical scale, due to its nature of measuring entities in a cluster.Taking figure 1 as an example, the numbers are only representing the values of all the attributes. This type of scale is commonly used to measure items that classify individuals, firms, brands, product or any other entities into categories where order is not important (). It is a categorical scale with its basic applied rule of different entities receive different value (Meyer, Gamst & Guarino, n.d). Typically, there are four scales of measurement namely nominal, ordinal, interval, and ratio scales of measurement.This type of scaling is said to be the most basic measurement. Gracenote database update jaguarTo sum up, each of the observation belongs to its own category and such an an observation does not represent “more” or “less” than another observation.Upon completion of the questionnaires, each item response will be analysed or in certain cases summated in order to obtain the score. There is neither significant quantitative dimension implied in this type of scaling nor the implication that one entity is in any way “more” than another (Meyer, Gamst & Guarino, n.d). In nominal scale, the numbers have no arithmetic properties, instead they just merely act as the labels (). For instance, in nominal scale number 3 which represents Geography association does not have higher actual value than number 2 that represents Mathematics. The advantage of treating this individual Likert items as ordinal data is that Likert responses can be portrayed into several statistical charts including bar charts. Thus, by treating it as merely ordinal would be inappropriate as the information would be lost (). On the other hand, often (referring to the example above) the wording of response levels about a middle category clearly implies symmetry of response levels, hence, such an item would fall between ordinal-level and interval-level measurement. This statement is in agreement with Jamieson (2004) that Likert scales fall within the ordinal level of measurement because response categories have the rank order, however, the interval between values cannot be presumed equal. When using Likert items of only five levels, researcher cannot make assumption that respondents perceive all the adjacent levels as being in equal distant, thus regard item as an ordinal data (). Such classification would depend on the arrangement of the individual Likert items. They had assumed Likert-type data to be measured as an interval-level measurement. Recently, Santina (2003) and Hren (2004) had published their papers which had used Likert scale to describe data using means and standard deviation. Responses to several Likert questions may be summed, provided that all the questions use the same Likert scale and the scale is an approximation to an interval scale (). This is because the calculation for the mean and the standard deviation are inappropriate for ordinal data (Blaikie 2003) as the numbers used to represent the data are generally the verbal statements (Jamieson 2004).Treating ordinal scales as interval scales has long been controversial. Validity And Reliability Psychology Free From ErrorThe chi-square, Cochran Q, or McNemar test is common statistical procedures used after this transformation ().According to Thanasegaran (2009), reliability is the degree to which measures are free from error and therefore yield consistent results. In addition, data from Likert scales are sometimes reduced to the nominal level by combining all “agree” and “disagree” responses into two categories of “accept” and “reject”. Jamieson (2004) is among researcher who was against this assumption.
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