Evidence map›Paper›PMID 22478326›Full record

ArticleThe Behavior analyst1999

Statistical inference in behavior analysis: Having my cake and eating it?

M Davison

Abstract read
In one paragraph

Article in The Behavior analyst, 1999. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Tutorial: Small-N Power Analysis.Perspectives on behavior science · 2019
    Article
  5. Article
  6. Review
  7. Go forth and be variable.The Behavior analyst · 2013
    Article
  8. Review
  9. Article
  10. Article
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

1 author.

M Davison

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Using simple, nonparametric statistical procedures can formalize the process of letting data speak for themselves, and can eliminate the gratuitous dismissal of deviant data from subjects or conditions. These procedures can act as useful discriminative stimuli, both for behavior analysts and for those from other areas of psychology who occasionally sample our journals. I also argue that changes in publication policies must change if behavior analysts are to accurately discriminate between real, reliable effects (hits) and false alarms.

Identifiers

PMID22478326
PMCPMC2731347

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.