TagRuler: Interactive Tool for Span-Level Data Programming by Demonstration

AbstractA key step in understanding the results of biological experiments is visualization of the data. Many laboratory experiments contain a range of measurements that exist within a hierarchy of interdependence. An automated way to visualise and interrogate experimental data would: 1) lead to improved understanding of the results, 2) help to determine which statistical tests should be performed, and 3) easily identify outliers and sources of batch effects. Unfortunately, existing graphing solutions often demand expertise in programming, require considerable effort to import and examine such multi-level data, or are unnecessarily complex for the task at hand. Here we present LAB-AID (Laboratory Automated Interrogation of Data), an interactive tool specifically designed to automatically visualize and query hierarchical data resulting from biological experiments.

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New Evidence on the Construct Validity of the ASI-3 and the Dimensional Conceptualization of Trait Anxiety Sensitivity From IRT Modeling

European Journal of Psychological Assessment ◽

10.1027/1015-5759/a000284 ◽

2017 ◽

Vol 33 (3) ◽

pp. 181-189 ◽

Cited By ~ 2

Author(s):

Christoph J. Kemper ◽

Michael Hock

Keyword(s):

Construct Validity ◽

Anxiety Sensitivity ◽

Latent Class ◽

Dimensional Structure ◽

Sensitivity Index ◽

Response Scale ◽

Established Risk Factor ◽

Irt Models ◽

Level Data ◽

Extreme Response

Abstract. Anxiety Sensitivity (AS) denotes the tendency to fear anxiety-related sensations. Trait AS is an established risk factor for anxiety pathology. The Anxiety Sensitivity Index-3 (ASI-3) is a widely used measure of AS and its three most robust dimensions with well-established construct validity. At present, the dimensional conceptualization of AS, and thus, the construct validity of the ASI-3 is challenged. A latent class structure with two distinct and qualitatively different forms, an adaptive form (normative AS) and a maladaptive form (AS taxon, predisposing for anxiety pathology) was postulated. Item Response Theory (IRT) models were applied to item-level data of the ASI-3 in an attempt to replicate previous findings in a large nonclinical sample (N = 2,603) and to examine possible interpretations for the latent discontinuity observed. Two latent classes with a pattern of distinct responses to ASI-3 items were found. However, classes were indicative of participant’s differential use of the response scale (midpoint and extreme response style) rather than differing in AS content (adaptive and maladaptive AS forms). A dimensional structure of AS and the construct validity of the ASI-3 was supported.

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Modeling Intraindividual Variability in Three-Level Multilevel Models

Methodology ◽

10.1027/1614-2241/a000150 ◽

2018 ◽

Vol 14 (3) ◽

pp. 95-108 ◽

Cited By ~ 4

Author(s):

Steffen Nestler ◽

Katharina Geukes ◽

Mitja D. Back

Keyword(s):

Multilevel Model ◽

Multilevel Models ◽

Mixed Effects ◽

Repeated Measurements ◽

Scale Model ◽

Suggested Approach ◽

Psychological Study ◽

Level Data ◽

Ecological Momentary ◽

Momentary Assessment

Abstract. The mixed-effects location scale model is an extension of a multilevel model for longitudinal data. It allows covariates to affect both the within-subject variance and the between-subject variance (i.e., the intercept variance) beyond their influence on the means. Typically, the model is applied to two-level data (e.g., the repeated measurements of persons), although researchers are often faced with three-level data (e.g., the repeated measurements of persons within specific situations). Here, we describe an extension of the two-level mixed-effects location scale model to such three-level data. Furthermore, we show how the suggested model can be estimated with Bayesian software, and we present the results of a small simulation study that was conducted to investigate the statistical properties of the suggested approach. Finally, we illustrate the approach by presenting an example from a psychological study that employed ecological momentary assessment.

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