Evidence map›Paper›PMID 25187323›Full record

ArticlePsychometrika2016

Human Psychophysical Functions, an Update: Methods for Identifying their form; Estimating their Parameters; and Evaluating the Effects of Important Predictors.

Diana E Kornbrot

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Article in Psychometrika, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Time Production Intensively Studied in One Observer.Journal for person-oriented research · 2022
    Article
  2. 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.

Diana E KornbrotDepartment of Psychology, University of Hertfordshire, College Lane Hatfield, Hertfordshire, AL10 9AB, UK. d.e.kornbrot@herts.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Stevens' power law for the judgments of sensation has a long history in psychology and is used in many psychophysical investigations of the effects of predictors such as group or condition. Stevens' formulation [Formula: see text], where [Formula: see text] is the psychological judgment, P is the physical intensity, and [Formula: see text] is the power law exponent, is usually tested by plotting log [Formula: see text] against log (P). In some, but by no means all, studies, effects on the scale parameter, [Formula: see text], are also investigated. This two-parameter model is simple but known to be flawed, for at least some modalities. Specifically, three-parameter functions that include a threshold parameter produce a better fit for many data sets. In addition, direct non-linear computation of power laws often fit better than regressions of log-transformed variables. However, such potentially flawed methods continue to be used because of assumptions that the approximations are "close enough" as to not to make any difference to the conclusions drawn (or possibly through ignorance the errors in these assumptions). We investigate two modalities in detail: duration and roughness. We show that a three-parameter power law is the best fitting of several plausible models. Comparison between this model and the prevalent two parameter version of Stevens' power law shows significant differences for the parameter estimates with at least medium effect sizes for duration.

Indexed as

Models, StatisticalPsychometricsPsychophysicsHumansdurationindividual differencesmagnitude estimationmagnitude productionroughnessStevens’ power law

Identifiers

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Registered trials

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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.