scholarly journals Differential endorsement of suicidal ideation and attempt in bipolar versus unipolar depression: a testlet response theory analysis

2016 ◽  
Vol 200 ◽  
pp. 67-73 ◽  
Author(s):  
Lauren M. Weinstock ◽  
David Strong ◽  
Lisa A. Uebelacker ◽  
Ivan W. Miller
Keyword(s):  
Suicidal Ideation ◽  
Unipolar Depression ◽  
Response Theory ◽  
Theory Analysis ◽  
Testlet Response Theory

Investigating the Dynamics of Suicidal Ideation

Crisis ◽  
2018 ◽  
Vol 39 (1) ◽  
pp. 65-69 ◽  
Author(s):  
Nina Hallensleben ◽  
Lena Spangenberg ◽  
Thomas Forkmann ◽  
Dajana Rath ◽  
Ulrich Hegerl ◽  
...  
Keyword(s):  
Suicidal Ideation ◽  
Small Sample Size ◽  
Unipolar Depression ◽  
Small Sample ◽  
History Of ◽  
Severity Of Depression ◽  
Ecological Momentary ◽  
Depressive Episodes ◽  
Ema Method ◽  
Shed Light

Abstract. Background: Although the fluctuating nature of suicidal ideation (SI) has been described previously, longitudinal studies investigating the dynamics of SI are scarce. Aim: To demonstrate the fluctuation of SI across 6 days and up to 60 measurement points using smartphone-based ecological momentary assessments (EMA). Method: Twenty inpatients with unipolar depression and current and/or lifetime suicidal ideation rated their momentary SI 10 times per day over a 6-day period. Mean squared successive difference (MSSD) was calculated as a measure of variability. Correlations of MSSD with severity of depression, number of previous depressive episodes, and history of suicidal behavior were examined. Results: Individual trajectories of SI are shown to illustrate fluctuation. MSSD values ranged from 0.2 to 21.7. No significant correlations of MSSD with several clinical parameters were found, but there are hints of associations between fluctuation of SI and severity of depression and suicidality. Limitations: Main limitation of this study is the small sample size leading to low power and probably missing potential effects. Further research with larger samples is necessary to shed light on the dynamics of SI. Conclusion: The results illustrate the dynamic nature and the diversity of trajectories of SI across 6 days in psychiatric inpatients with unipolar depression. Prediction of the fluctuation of SI might be of high clinical relevance. Further research using EMA and sophisticated analyses with larger samples is necessary to shed light on the dynamics of SI.

Introduction to bifactor polytomous item response theory analysis

2017 ◽  
Vol 60 ◽  
pp. 41-63 ◽  
Author(s):  
Michael D. Toland ◽  
Isabella Sulis ◽  
Francesca Giambona ◽  
Mariano Porcu ◽  
Jonathan M. Campbell
Keyword(s):  
Item Response Theory ◽  
Item Response ◽  
Response Theory ◽  
Theory Analysis ◽  
Polytomous Item ◽  
Item Response Theory Analysis ◽  
Polytomous Item Response Theory ◽  
Polytomous Item Response

scholarly journals Investigating diagnostic bias in autism spectrum conditions: An item response theory analysis of sex bias in the AQ-10

2016 ◽  
Vol 10 (5) ◽  
pp. 790-800 ◽  
Author(s):  
Aja Louise Murray ◽  
Carrie Allison ◽  
Paula L. Smith ◽  
Simon Baron-Cohen ◽  
Tom Booth ◽  
...  
Keyword(s):  
Item Response Theory ◽  
Item Response ◽  
Autism Spectrum ◽  
Autism Spectrum Conditions ◽  
Sex Bias ◽  
Response Theory ◽  
Theory Analysis ◽  
Diagnostic Bias ◽  
Item Response Theory Analysis

scholarly journals Examination of Different Item Response Theory Models on Tests Composed of Testlets

2017 ◽  
Vol 6 (4) ◽  
pp. 113
Author(s):  
Esin Yilmaz Kogar ◽  
Hülya Kelecioglu
Keyword(s):  
Item Response Theory ◽  
Sample Size ◽  
Item Response ◽  
Data Sets ◽  
Meaningful Difference ◽  
Response Theory ◽  
Size Change ◽  
Data Set ◽  
Testlet Response Theory ◽  
Item Response Theory Models

The purpose of this research is to first estimate the item and ability parameters and the standard error values related to those parameters obtained from Unidimensional Item Response Theory (UIRT), bifactor (BIF) and Testlet Response Theory models (TRT) in the tests including testlets, when the number of testlets, number of independent items, and sample size change, and then to compare the obtained results. Mathematic test in PISA 2012 was employed as the data collection tool, and 36 items were used to constitute six different data sets containing different numbers of testlets and independent items. Subsequently, from these constituted data sets, three different sample sizes of 250, 500 and 1000 persons were selected randomly. When the findings of the research were examined, it was determined that, generally the lowest mean error values were those obtained from UIRT, and TRT yielded a mean of error estimation lower than that of BIF. It was found that, under all conditions, models which take into consideration the local dependency have provided a better model-data compatibility than UIRT, generally there is no meaningful difference between BIF and TRT, and both models can be used for those data sets. It can be said that when there is a meaningful difference between those two models, generally BIF yields a better result. In addition, it has been determined that, in each sample size and data set, item and ability parameters and correlations of errors of the parameters are generally high.

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