Evidence map›Paper›PMID 35342875›Full record

ArticlePerspectives on behavior science2022

Implementing Automated Nonparametric Statistical Analysis on Functional Analysis Data: A Guide for Practitioners and Researchers.

Michael P Kranak, Scott S Hall

Abstract read
In one paragraph

Article in Perspectives on behavior science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Michael P KranakDepartment of Human Development and Child Studies, Oakland University, Rochester, MI USA.
Scott S HallDepartment of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Road, Room 1365, Stanford, CA 94305-5795 USA.ORCID 0000-0003-4797-1819

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Functional analysis (FA) is an integral component of behavioral assessment and treatment given that clinicians design behavioral treatments based on FA results. Unfortunately, the interrater reliability of FA data interpretation by visual analysis can be inconsistent, potentially leading to ineffective treatment implementation. Hall et al. (2020) recently developed automated nonparametric statistical analysis (ANSA) to facilitate the interpretation of FA data and Kranak et al. (2021) subsequently extended and validated ANSA by applying it to unpublished clinical data. The results of both Hall et al. and Kranak et al. support ANSA as an emerging statistical supplement for interpreting FA data. In the present article, we show how ANSA can be applied to interpret FA data collected in clinical settings in multielement and pairwise designs. We provide a detailed overview of the calculations involved, how to use ANSA in practice, and recommendations for its implementation. A free web-based application is available at https://ansa.shinyapps.io/ansa/. Supplementary Information: The online version contains supplementary material available at 10.1007/s40614-021-00290-2.

Indexed as

Data interpretationFunctional analysisStatistical analysisVisual analysis

Identifiers

PMID35342875
PMCPMC8894515

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.