PARADIGM SHIFT AND MEASUREMENT ISSUES OF SUBJECTIVE WELL-BEING.

Debdulal Dutta Roy

Psychology Research Unit

Indian Statistical Institute, Kolkata

WHAT IS SWB ? , DIFFERENTIAL PERSPECTIVES

QOL

SWLS

POS

NEG

HAPPINESS

PWB

Dr. D. Dutta Roy, ISI., Kolkata. Venue: National Seminar on‘Wellbeing across Lifespan’ from 25 – 27 October, 2017

Legend

❏ QOL - WHO

❏ SWLS-Diener and

others (1985)

❏ Positive and Negative

Affect -watson (1988)

❏ Happiness: Peter Hills

and Argyle (2002)

❏ Psychological well being

- Ryff and Ryan Hedonistic distance:

❖ Both QOL and SWLS are

judgment oriented..more

experiential and cognive.

❖ POS and NEG are

affective.

❖ Happiness and PWB are

from humanistic

approach.

Paradigm shift

Hypothesis driven

•Literature Review & Hypothesis formulation•Sampling and structured data collection•Guided data analysis and theory development

Psychoinformatics (Data Driven)

•No Hypothesis but research questions•Data warehouse•Data retrieving•Data cleaning•Data mining•Pattern recognition•Discovery of Knowledge

Hypothesis Driven Model

Reliability

Reliable SWB score = SWB score - Measurement ErrorMeasurement error is broadly classified into two - Systematic and Random. Presence of errors affects the validation of instrument and related theories.

Error margin

Factors affecting the width of the confidence interval include the size of the sample, the confidence level, and the variability in the sample.

A larger sample size normally will lead to a better estimate of the population parameter.

Systematic errors

Items of the instrument may suffer from fixed errors. PANAS is commonly used instrument to assess subjective well-being. It is assumed that SWB has affective component. PANAS measures the positive and negative feeling component of SWB. Confirmatory factor analysis shows good discriminant validity. But some items of PANAS measure motivation not feeling (Diener, 2002).

Random errors

A random error, as the name suggests, is random in nature and very difficult to predict. It occurs because there are a very large number of parameters beyond the control of the experimenter that may interfere with the results of the experiment.

For example, mood and motivation of respondent affects scores.

Minimizing Measurement Error

• Pilot test the instrument, get feedback regarding extent of easiness or difficulty from respondents and how test environment affects the performance.

• Train the interviewers and observers about standard instruction, double check the data whether respondent misses any thing or not.

• Machine checking the data. • Use multiple measures and check relationship.• Random sampling • Increase in sample size.• Good rapport system.

Experimental design

• True experimental designs that involve experimenter manipulation of the independent variable and experimenter control over the assignment of participants to treatment conditions.

• It includes several Randomized group designs like one way group design, Block design, Latin square design, Factorial design.

Study: Effect of muscular relaxation on SWB of Schizophrenia.

Pre-post or post https://www.ncbi.nlm.nih.gov/pubmed/21402653

Quassi-Experimental design

• Ex-post facto research is systematic empirical inquiry in which the scientist does not have direct control of independent variables because their manifestations have already occurred or because they are inherently not manipulated.

Study: Effect of Diabetes Self Management Educational Training Program on patient attitudes to diabetes and their relations with the depression were explored.

Regression

• Regression is a statistical measure to determine the strength of the relationship between one dependent variable (usually denoted by Y) and a series of other changing variables (known as independent variables).

• A. Simple regressionB. Multiple regressionC. Stepwise multiple regressionD. Path analysisE. Structural equation modellingF. Covariates

Path-Analysis: CFA of Positive and Negative affective Schedule

Confirmatory factor analysis and temporal invariance of the Positive and Negative Affect Schedule (PANAS)

Structural equation model

•Structural equation models are often used to assess unobservable 'latent' constructs.

•They often invoke a measurement model that defines latent variables using one or more observed variables, and a structural model that imputes relationships between latent variables.

Path diagram for Mediational Analysis

• A path diagram that illustrates the mediational relationship and indicates beta weights is most useful.

Discriminant function analysis

• Discriminant function analysis is a statistical analysis to predict a categorical dependent variable (called a grouping variable) by one or more continuous or binary independent variables (called predictor variables).

• The main purpose of a discriminant function analysis is to predict group membership based on a linear combination of the interval variables.

• The procedure begins with a set of observations where both group membership and the values of the interval variables are known.

• Discriminant function analysis is reversed of multivariate analysis of variance (MANOVA). In MANOVA, the independent variables are the groups and the dependent variables are the predictors.

The Strong Discriminating Predictors

Categorical grouping

Correspondence map

Data Driven Model

Text Mining

• Research Question

• Data Reservoir: Select noise free search engines where in research answers are available.

• Data Cleaning: Select abstracts using inclusion and exclusion criteria.

• Coding and Node construction.

• Text classification using frequency of research.

• Pattern recognition.

• Discovery of Knowledge.

Thank You