Do we need statistic quality criteria?

Topics: Validity, Psychometrics, Measurement Pages: 8 (2222 words) Published: June 20, 2014


Criterions of Measurement
Why do we need criterions of measurement?
What problems may this application includes?

Do we need statistic quality criteria?
Table of Contents
Chapter 1 - Introduction4
Chapter 2 – Criterions of Measurements5
1.Objektivitity5
2.Reliability5
3.Validity6
3.1 Construct Valdity………………………………………………………………………... 3.2 Criterion Validity………………………………………………………………………… 3.2.1 Convergent Validity………………………………………………………………… 3.2.2 Discriminant Validity……………………………………………………………….. 3.2.3 Concurrent Validity………………………………………………………………… 3.3 Content Validity…………………………………………………………………………. 3.4 Ecological Validity6

4. Acceptably…………………………………………………………………………………. 5. Economic…………………………………………………………………………………….. Chapter 3 – Feedback/Result…………………………………………………………………

Chapter 1 – Introduction

Why do we need criterions of measurement?

With the quantification of relevant study characteristics with questionnaires, tests or observations the research aims to provide the comparability of data securely. The intention is to compare statistical analysis methods and dependencies. With the transformation into quantitative variables a rationalization effect is desired. In this way extensive data can be reduced to its core. To check the comparability required for that, quality criteria have been developed. These are according to current interpretation higher if the standardization of the research’s content, the course of the investigation and the setting is easily realizable.

There are five different types of criterions of measurement. These five criterions of measurement are divided into two groups. The main group and the sub group. Objectivity, Reliability and Validity belong to the main group. Acceptability and Economy are the two parts of the subgroup. This paper is focused on the main group.

Chapter 2 – Criterions of Measurements
1.Objectivity

Objectivity is the extent to which a test result in implementation, analysis and interpretation can be influenced by an investigator or if more come to matching results. Neither the implementation nor the analysis and interpretation carried out by different researchers may therefore produce different results. The implementing objectivity requires that the test result is unaffected by the user. The interpretation of objectivity requires that individual interpretations can not be used towards the interpretation of a result.

For example to measure the screw length by a calibrated measuring equipment is an objective measurement but the survey of employees by their team leader for the leadership is very subjective. 2.Reliability

Reliability indicates the reliability of a measurement method. An investigation is described as reliable if it comes to the same conclusion at a repetition of the measurement under the same conditions. It can be inter alia determined by a repeat examination (test-retest method) or other equivalent test (parallel test method). The measure is the reliability coefficient and it is defined by the correlation of the two investigations.

An example of a reliable question is "How many employees has your department?" In contrast the question "How many teamplaying employees has your department?" The second question has a lower reliability because it is unclear who is defined as a "team player" and therefore different opinions can come into existence.

3.Validity
Some people say that there is no validity but indeed there are quite different kinds of validity. This is certainly true but they have in common: validity or validity of these measurements describe the degree of accuracy with which a method measures what it purports to measure. An intelligence test for example is only valid when intelligence activities are measured and not primarily the steadiness. A test has content that is "true" the problem is to determine that. The name of "intelligence" (as well as "aggression",...
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