PRESENTATION TOPIC : RELIABILITY THEORY PRESENTED BY : ABDUL KHALIQ KHAN PRESENTED TO : SIR MUDASSIR FAROOQI SUBJECT : ADVANCE RESEARCH PROGRAM : MCOM 2 ND

RESEARCH WHAT IS A RELIABILITY? WHAT IS THE MEASURE OF RELIABILITY? WHY WE NEED RELIABILITY? STANDARD OF RELIABILITY IN SOCIAL SCIENCES? OUR DATA RELIABILITY?

Reliability Means "repeatability" or "consistency". A measure is considered reliable if it would give us the same result over and over again (assuming that what we are measuring isn't changing!). There are four general classes of reliability estimates, each of which estimates reliability in a different way.

Reliabilty (continued) Inter-Rater or Inter-Observer Reliability Test-Retest Reliability Parallel-Forms Reliability Internal Consistency Reliability

What Is Reliability Theory? Reliability theory is a general theory of systems failure developed by mathematicians:

Reliability theory was historically developed to describe failure and aging of complex electronic (military) equipment, but the theory itself is a very general theory based on probability theory and systems approach.

Why Do We Need Reliability-Theory Approach? Because it provides a common scientific language (general paradigm) for scientists working in different areas of aging research. Reliability theory helps to overcome disruptive specialization and it allows researchers to understand each other. May be useful for integrative studies of aging. Provides useful mathematical models allowing to explain and interpret the observed data and findings.

Counterbalancing Why you need to counterbalance: To avoid order effects – some items may influence other items To avoid fatigue effects – subjects get tired and performance on later items suffers To avoid practice effects – subjects learn how to do the task and performance on later items improves

Validity Is the translation from concept to operationalization accurately representing the underlying concept. Does it measure what you think it measures. This is more familiarly called Construct Validity.

Validity The standard of validity in quantitative research requires researchers to demonstrate both internal and external validity. Internal validity is the degree to which the results of a study can be accurately interpreted as meaning what they appear to mean. External validity is the degree to which the results of a study are contrived or artificial, or put another way, the degree to which the results apply to the outside world. Listed below are a number of issues identified by Campbell and Stanley (1963) as potential threats to the internal and external validity of a study:

Types of Construct Validity Translation validity (Trochims term) –Face validity –Content validity Criterion-related validity –Predictive validity –Concurrent validity –Convergent validity –Discriminant validity

Generalizability As mentioned above, the standard of generalizability in quantitative research requires researchers to show the degree to which the results of a study can justifiably be generalized, or applied, to a larger population or to other similar groups. A study can be extremely well designed, controlled, and internally valid, but lack external validity. The problem is that controls, when introduced, may make the study artificial and thus limit the external validity.

Replicability The standard of replicability in quantitative research requires researchers to provide enough information about a study to allow other researchers to replicate or repeat the study exactly as it was originally conducted. The replicability of a quantitative study can be improved by thorough and complete descriptions of: (1) the participants in the study and how they were selected, (2) the instruments used in the study as well as arguments for their reliability and validity, and (3) the procedures followed in collecting the data, scoring or coding the instruments, and analyzing the results (see Brown, 1988, ch. 5 for a more complete discussion of what should be included to make a study adequately replicable).

Reliability The standard of reliability in quantitative research requires researchers to demonstrate both (1) the reliability of the instruments used in their studies and (2) the reliability of the results of their studies. Reliability of instruments is concerned with the degree to which the results of a questionnaire, test, or other measuring instrument are consistent. Addressing this issue typically means answering the question: To what degree would the results be the same if the instrument were administered repeatedly? Similarly, the reliability of the results of a study is concerned with the degree to which the results would be likely to reappear if the study were replicated under the same conditions.

Thank You