Test
CALL FOR PARTICIPATION
PSYCHOLOGY RESEARCH UNIT
INDIAN STATISTICAL INSTITUTE, KOLKATA
ORIENTATION TRAINING ON ADVANCED APPLIED PSYCHOMETRICS (TAPP23)
(27-28TH DECEMBER, 2023, 11-4 PM, HYBRID MODE)
Psychology Research Unit, Indian Statistical Institute, invites application for 'ORIENTATION TRAINING ON ADVANCED APPLIED PSYCHOMETRICS'. Classical test theory(CTT) is sample-dependent, as reliability coefficients can differ between groups, impacting the generalizability of findings.Another critical drawback is the failure to address item difficulty and discrimination independently. CTT treats items as interchangeable, neglecting the nuances of each item's contribution to measurement precision. This oversimplification limits the test developer's ability to identify and modify specific problematic items, hindering the refinement of assessments.In conclusion, while Classical Test Theory has played a significant role in the history of psychometrics, its limitations in accounting for measurement error variability and individual item characteristics underscore the need for more sophisticated approaches. Aim of this workshop is to disseminate (a) classical test theory, (b)hierarchical cluster analysis of items, (c) item response theory, and (d) structural equation modelling. This knowledge is relatively new in Indian researches in Psychology. This model is useful in Machine learning for computer adaptive testing. Finally, it will be used for personalized testing.
Educational Qualification: P.G. in Psychology/Education or related areas.
Eligibility: faculties, researchers and project workers.Knowledge of Statistics and R-studio.
Application: Please fill out the form (click here)
Certificate: One certificate will be provided after submission of the assignment.
Mode: Online in Zoom. Offline: At the venue of the Indian Statistical Institute.
TA & DA: Not available.
Recording: No you tube video will be available.
Important Dates: Registration starts: 12th December, 2023
Registration completes: 20th December, 2023.
Declaration of selected trainees: 23 rd December,2023.
Class starts: 27th December,2023
Convener
Dr. Garga Chattopadhyay,
Assistant Professor
Psychology Research Unit
Indian Statistical Institute, Kolkata-700108
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ORIENTATION TRAINING ON ADVANCED APPLIED PSYCHOMETRICS (TAPP23)
(27-28TH DECEMBER, 2023, 11-4 PM, HYBRID MODE)
27.12.2023
11 -00 Inauguration
Dr. Niladri Shekhar Das, Prof-in-charge, SSD.
Dr. Garga Chattopadhyay, Psychology Research Unit.
Dr. Debdulal Dutta Roy, Psychology Research Unit.
12-00 Technical Session 1
Classical Test Theory and Limitations-Dr. Murshida Khatoon,
Department of Psychology, Geetam University, Visakhapattanam, A.P.
13-00 Lunch
14-00 Technical Session 2
Hierarchical cluster analysis of items-Dr. Debdulal Dutta Roy,
Psychology Research Unit.
15-00 Technical Session 3
R-Script- Dr. Debdulal Dutta Roy,
Psychology Research Unit.
16-00 Assignment
28.12.2023
11-00 Technical Session 4
Item-Response Theory – Dr. Sumona Datta, Government General Degree College, Singur.
13-00 Lunch
14-00 Technical Session 5
Structural Equation Modelling - Dr. Sushmita Chatterjee,Assistant Professor Of Economics,Maharaja
Manindra Chandra College.
16-00 Evaluation and Distribution of certificates.
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Research internship on 'RATING SCALE DESIGN AND ANALYSIS USING R-STUDIO
Psychology Research Unit, Indian Statistical Institute, invites application for Research internship on 'RATING SCALE DESIGN AND ANALYSIS USING R-STUDIO'. The internship includes training and writing paragraphs on following statistics - (a) Statistics of Mean differences, (b) Correlation statistics, (c) Regression analysis, and (d) Statistics for categorical data. This content will be used for teaching students of Psychology and Allied Sciences. This internship will be for two months. There will be 3 -day online classes per week from 2 to 3 PM. One certificate will be provided after submission of the contents. Applicant must have good knowledge in R-studio and relevant packages. Please submit your bio-data with application to the convener, Research internship, Psychology Research Unit, Indian Statistical Institute, Kolkata campus through e-mail: psy@isical.ac.in before 15th February, 2023.
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Application received from:
uditmaheshwari1035@gmail.com | Regression Analysis |
rashi7019@gmail.com |
Statistics of Mean differences |
|
urbeedutta@gmail.com |
Correlation statistics |
saswati.barat@gmail.com | Regression Analysis |
drmichellefernandes@gmail.com |
Correlation statistics |
moutushibhowmik01@gmail.com |
Statistics of Mean differences |
drsweta.patel@sxca.edu.in |
Statistics of Mean differences |
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Sample writing on small sample t-test
1. Definition, 2. Types, 3. Assumptions, 4. Uses, 5. Advantages, 6. Disadvantages, 7. Caes study.
Definition |
Definition A small sample t-test is a statistical test that is used to compare the means of two groups when the sample sizes are small (typically n<30) and the population standard deviation is unknown. This test is a variant of the Student's t-test, which is used to compare the means of two groups when the sample sizes are large and the population standard deviation is known. The small sample t-test uses the t-distribution to calculate the probability of obtaining the observed difference in means by chance, assuming that the two groups have equal variances. If the probability is less than a pre-specified level of significance (usually 0.05), then the difference is considered statistically significant. There are two types of small sample t-tests: the paired-sample t-test, which compares the means of two related groups, and the independent-sample t-test, which compares the means of two unrelated groups. The choice of which test to use depends on the research question and the study design. |
Types |
There are several types of mean difference statistics, which are used in different contexts and for different research questions. Here are some examples:
These mean difference statistics are commonly used in different fields of research, including psychology, education, medicine, and social sciences. The choice of which test to use depends on the research question, study design, and data characteristics. |
Assumptions |
The t-test is a statistical test that is used to compare the means of two groups. There are two types of t-tests: the independent samples t-test and the paired samples t-test. Both tests have certain assumptions that must be met for the test to be valid. Here are some common assumptions of the t-test:
If these assumptions are not met, the results of the t-test may not be reliable or valid. It is important to check the assumptions before conducting a t-test and to use alternative tests if the assumptions are violated. |
Uses |
Mean difference statistics are commonly used in statistics and research to quantify and compare the differences between the means of two or more groups or conditions. Here are some common uses of mean difference statistics:
Overall, mean difference statistics are a useful tool in statistics and research for quantifying and comparing differences between groups or conditions, and for evaluating the effectiveness of interventions or treatments. |
Advantages |
Mean difference statistics have several advantages that make them a popular tool for statistical analysis and research. Here are some advantages of mean difference statistics:
Overall, mean difference statistics have several advantages that make them a valuable tool for researchers and analysts. By quantifying and comparing the differences between groups or conditions, mean difference statistics provide a valuable tool for understanding differences and evaluating |
Disadvantages |
While mean difference statistics have many advantages, there are also some disadvantages that should be considered. Here are some disadvantages of mean difference statistics:
Overall, mean difference statistics have some disadvantages that should be considered when using them for statistical analysis and research. It is important to carefully consider the assumptions of the statistical test, the characteristics of the data, and the limitations of the test, in order to make valid and reliable conclusions. |
Case study |
Here is an example of a case study that involves the use of mean difference statistics: A researcher is interested in whether a new training program improves employee productivity. The researcher randomly assigns 50 employees to either a training group or a control group. The training group receives the new training program, while the control group does not receive any additional training. After one month, the researcher measures the productivity of both groups. The productivity scores are normally distributed, with a mean of 75 for the control group and a mean of 85 for the training group. The standard deviation for both groups is 5. To determine whether the training program improves productivity, the researcher uses a two-sample t-test. The null hypothesis is that there is no difference in productivity between the training group and the control group, while the alternative hypothesis is that the training program improves productivity. The calculated t-value for the mean difference is 10, and the p-value is less than .001. Since the p-value is less than .05, the researcher rejects the null hypothesis and concludes that the training program improves productivity. In this case, the mean difference statistics, specifically the two-sample t-test, allowed the researcher to compare the means of two groups and determine whether the difference was statistically significant. By using mean difference statistics, the researcher was able to evaluate the effectiveness of the training program and make evidence-based decisions about whether to implement it more widely. |
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Bivariate | Multivariate | |
3.1 Mean differences 3.2 Correlation and regression 3.3 Chi-square test |
4.1 Analysis of variance 4.6 Multiple regression |
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Bivariate
3.1 Mean differences
3.2 Correlation and regression
3.3 Chi-square test
Multivariate
4.1 Analysis of variance
4.2 Multivariate analysis of variance
4.3 Analysis of covariance
4.4 Multivariate analysis of Covariance(MANCOVA)
4.6 Multiple regression
4.7 Discriminant function analysis
4.8 Principal component analysis
4.9 Confirmatory factor analysis
4.10 Cluster analysis
4.11 Structural equation modeling
CALL FOR PARTICIPATION
PSYCHOLOGY RESEARCH UNIT
INDIAN STATISTICAL INSTITUTE, KOLKATA
WORKSHOP ON RATING SCALE DESIGN AND ANALYSIS USING R-STUDIO (CODE:RSD22)
(21-25TH NOVEMBER, 2022, 11-4 PM, HYBRID MODE)
OBJECTIVE:
Aim of this workshop is to disseminate knowledge to the faculties and Ph.D fellows about Rating scale design, analysis of data through R-Script. Recently on 4th November, 2022, Psychology Research Unit of the Indian Statistical Institute completed one day training on 'Norm estimation based on Summated Rating scale'. Ph.D. scholars and teaching faculties of different universities and research institutes participated in this certificate course. It has been felt that multivariate statistics play an important role in analysis of summated rating scale. Psychology Research Unit trains its scholars about application of multivariate statistics in psychological research. There is a dearth of research on it in the doctoral dissertations of psychology due to inadequate understanding about basic assumptions, tools and the know-how about applications of multivariate statistics. Aim of this workshop is to disseminate knowledge about the tools, their assumptions and applications in analysis of summated rating scale based data.
APPLICATION: https://docs.google.com/forms/d/e/1FAIpQLSfFQOwNVsk1ep8uSeAgquXOHlCRsgs_...
SHORT FORM: https://forms.gle/pvHsJ7PyZkzRHUZSA
Registration: Rs. 1330 (One Thousand Three hundred thirty only. including GST).
Payment procedure: A/C NO. 0071050000118, IFSC: PUNB0397700. IN FAVOUR OF: INDIAN STATISTICAL INSTITUTE
TENTATIVE SCHEDULE OF THE PROGRAME:
DATE & TIME 21ST NOVEMBER MONDAY
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EVENT & TIME |
RESOURCE PERSON |
11:00-12:00PM |
|
DR D. DUTTA ROY, HEAD & ASSOCIAT E PROFESSOR, PSYCHOLOGY RESEARCH UNIT, ISI RUCHIRA GANGOPADHYAY (Student Coordinator) |
12:00-12:15PM |
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- |
12:15-1:00PM |
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DR D. DUTTA ROY, HEAD & ASSOCIAT E PROFESSOR, PSYCHOLOGY RESEARCH UNIT, ISI. |
1:00-2:00PM |
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- |
2:00-4:00 PM |
|
DR. SUMONA DUTTA, ASSISTANT PROFESSOR OF PSYCHOLOGY AT GOVERNMENT GENERAL DEGREE COLLEGE, SINGUR |
DATE & TIME 22ND NOVEMBER TUESDAY |
EVENT |
RESOURCE PERSON |
11:00-1:00PM |
|
DR D. DUTTA ROY, HEAD & ASSOCIAT E PROFESSOR, PSYCHOLOGY RESEARCH UNIT, ISI. |
1:00-2:00PM |
|
- |
2:00-3:00 PM |
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DR. MURSHIDA KHATOON, ASSISTANT PROFESSOR, DEPARTMENT OF PSYCHOLOGY, GEETAM UNIVERSITY, VISAKHAPATTANAM |
3:00-4:00 PM |
|
DR. D. DUTTA ROY, HEAD & ASSOCIAT E PROFESSOR, PSYCHOLOGY RESEARCH UNIT, ISI. |
DATE & TIME 23RD NOVEMBER WEDNESDAY |
EVENT |
RESOURCE PERSON |
11:00-12:00PM |
|
DR. SHIVANI SANTOSH HEAD, DEPARTMENT OF APPLIED PSYCHOLOGY, NEOTIA UNIVERSITY. |
12:00-1:00 PM |
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DR. ANURUPA KUNDU,ASSISTANT PROFESSOR OF PSYCHOLOGY AT ST. XAVIERS UNIVERSITY, KOLKATA. |
1:00-2:00 PM |
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2:00-3:00 PM |
|
DR. SUSHMITA CHATTERJEE,ASSISTANT PROFESSOR OF ECONOMICS AT MAHARAJA MANINDRA CHANDRA COLLEGE |
3:00-4:00 PM) |
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DR. SUSHMITA CHATTERJEE,ASSISTANT PROFESSOR OF ECONOMICS AT MAHARAJA MANINDRA CHANDRA COLLEGE |
DATE & TIME 24th NOVEMBER THURSDAY |
EVENT |
RESOURCE PERSON |
11:00-1:00 PM |
|
DR. D. DUTTA ROY HEAD & ASSOCIATE PROFESSOR, PSYCHOLOGY RESEARCH UNIT, ISI. |
1:00-2:00 PM) |
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- |
2:00-4:00 PM) |
|
DR. D. DUTTA ROY HEAD & ASSOCIATE PROFESSOR, PSYCHOLOGY RESEARCH UNIT, ISI. |
DATE & TIME 25th NOVEMBER THURSDAY |
EVENT & TIME |
RESOURCE PERSON |
11:00-1:00 PM |
|
DR. SUSHMITA MUKHOPADHYAY ASSISTANT PROFESSOR, INDIAN INSTITUTE OF TECHNOLOGY, KHARAGPUR |
1:00-2:00 PM |
|
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2:00-4:00 PM |
|
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ORGANIZING COMMITTEE
Dr. Debdulal Dutta Roy, Head, Psychology Research Unit, Indian Statistical Institute, Kolkata.
Dr. Garga Chattopadhyay, Asst. Professor, Psychology Research Unit, Indian Statistical Institute, Kolkata.
Ms. Sabornee Karmakar, Sr. Research Fellow, Psychology Research Unit, Indian Statistical Institute, Kolkata.
Ms.Ruchira Gangopadhyay, (Student co-ordinator), Psychology Trainee, Psychology Research Unit, Indian Statistical Institute, Kolkata.
Technical committee
Dr. Debdulal Dutta Roy, Head, Psychology Research Unit, Indian Statistical Institute, Kolkata.
DR SUSHMITA MUKHOPADHYAY, ASSISTANT PROFESSOR OF MANAGEMENT, IIT KHARAGPUR.
DR. SUMONA DUTTA, ASSISTANT PROFESSOR OF PSYCHOLOGY AT GOVERNMENT GENERAL DEGREE COLLEGE, SINGUR.
Ms. MURSHIDA KHATOON, ASSISTANT PROFESSOR OF PSYCHOLOGY AT GEETAM UNIVERSITY.
DR. ANURUPA KUNDU,ASSISTANT PROFESSOR OF PSYCHOLOGY AT ST. XAVIERS UNIVERSITY, KOLKATA..
DR. SUSHMITA CHATTERJEE,ASSISTANT PROFESSOR OF ECONOMICS AT MAHARAJA MANINDRA CHANDRA COLLEGE.
Administrative Committee
Mr. Dipak Sarkar, Section Officer.Psychology Research Unit, Indian Statistical Institute, Kolkata.
Mr. Swarup Ghara, Administrative assistant,Psychology Research Unit, Indian Statistical Institute, Kolkata.
Mr. Shyam Shaw, Administrative assistant,Psychology Research Unit, Indian Statistical Institute, Kolkata.
Please accept and send me the confirmation by 9th November, 2022.
Please write your name, contact details and probable slot on the following table.
TOPICS | RESOURCE PERSONS | Contact number | Designation | Affiliated Institute | Address | POSSIBLE DATES & TIME SLOT |
Analysis of variance and Co-variance | ||||||
Multiple regression | ||||||
Discriminant function analysis | ||||||
Exploratory and Confirmatory factor analysis | DR SUSMITA CHATTERJEE | 9831813312 | ASSISTANT PROFESSOR | MAHARAJA MANINDRA CHANDRA COLLEGE | 20 RAMKANTO BOSE STREET,SHYAMBAZAR, KOLKATA 700003 | 23RD NOVEMBER 2.30 PMTO 3.30 PM |
Cluster analysis | DR DEBDULAL DUTTA ROY | 9830010547 | HEAD & ASSOCIATE PROFESSOR | INDIAN STATISTICAL INSTITUTE | 203, BARACKPORE TRUNK ROAD, DUNLOP, KOLKATA-700108 |
22ND NOVEMBER 11-1 PM |
Structural equation modeling |
DR SUSMITA CHATTERJEE | 9831813312 | ASSISTANT PROFESSOR | MAHARAJA MANINDRA CHANDRA COLLEGE | 20 RAMKANTO BOSE STREET,SHYAMBAZAR, KOLKATA 700003 | 23RD NOVEMBER 3.45 PMTO 4.45 PM |
Item-Response Theory | DR SUMONA DATTA | 9432175390 | ASSISTANT PROFESSOR | GOVERNMENT GENERAL DEGREE COLLEGE, SINGUR | SINGUR WEST BENGAL 712409 |
21ST NOVEMBER 11 AM- 1 PM / 2 PM-4 PM |
With best wishes,
MULTIVARIATE STATISTICS IN ANALYSIS OF SUMMATED RATING SCALE
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Multivariate
4.1 Analysis of variance
4.2 Analysis of covariance
4.3 Multivariate analysis of variance
4.4 Multiple regression
4.5 Discriminant function analysis
4.6 Principal component analysis
4.7 Confirmatory factor analysis
4.7 Cluster analysis
4.8 Structural equation modeling
(PSYNORM22)
ONE DAY ONLINE TRAINING ON NORM ESTIMATION
FOR SUMMATED RATING SCALE USING R-STUDIO
NOVEMBER 4, 2022
Psychology Research Unit,
INDIAN STATISTICAL INSTITUTE
Report
Psychology Research Unit has successfully completed one online training on norm estimation for summated rating scale using R-Studio dated 4th November, 2022. Dr Sumona Datta, ex-research fellow of the unit, currently assistant professor of Department of Psychology, Government College, Singur, highlighted importance of Item response theory, norm estimation, and R-studio in the inaugural ceremony of the training. Ms. Ruchira Gangopadhyay of the unit assisted in teaching the course. Ph.D. fellows from renowned institutes and universities joined the program. At the valedictory session, we satisfied their Questions. All of them expressed satisfaction and they assured for the next training program with registration fees.
Tentative Programme Schedule |
ONLINE REGISTRATION |
Status of Registration |
Office bearers |
BACKGROUND
Summated Rating scale
Summated Rating scale is widely used instrument for classification of people based on norm. Aim of the present training is to disseminate knowledge about norm estimation. Norm estimation in summated rating scale requires few steps - item analysis, standard score computation and conversion to new score like T-score and finally classification of people based on the new classification categories. This training is useful for researchers interested in psychological test construction. Psychology Research Unit has designed many scales in research on educational, clinical, personality, career counselling, cognitive, finance and business psychology.
TOPICS:
1. Item analysis
2. Standard score determination.
3. T-score
4. Classification matrix
TENTATIVE PROGRAM SCHEDULE
Venue: Seminar room, Psychology Research Unit,7th floor, P.J.Auditorium,Indian Statistical Institute, 203,B.T.Road, Kolkata-700108.
4.10.22 | Event |
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11-11:30 | Inauguration Invocation, Speech, Self-introduction |
11:30-1:30 | Introduction to Norm |
1:30-2 | Lunch time(self-arranged) |
2-3 | Basic knowledge about R script -Item frame, item extraction, Item transformation, Outlier detection -Dr. D. Dutta Roy,Psychology Research Unit, Indian Statistical Institute, Kolkata. |
3-4 | Introduction to Characteristics of good psychological test - Ms. Sabornee Karmakar, Senior Research Fellow,Psychology Research Unit, Indian Statistical Institute, Kolkata. |
22.11.19(Wednesday) | Event |
11-1:30 | Item analysis - Item difficulty, Item discrimination - Dr. Atanu Kumar Dogra, Assistant Professor, Department of Psychology, University of Calcutta. |
1:30-2 | Lunch time(self-arranged) |
2-4 | Item shortening, Item validity -Ms.Sumona Datta, Assistant Professor, Adamas University, Kolkata |
Venue : Psychology Research Unit, Indian Statistical Institute, Kolkata.
Date and time : 21-22 nd November, 2019, 11 - 4PM.
:20Seats