Biomedical subjects

Lawrence T DeCarlo

Publications and source records attributed to Lawrence T DeCarlo.

10 recordsLinked to original sources

PubMed2007

The mirror effect and mixture signal detection theory.

The mirror effect for word frequency refers to the finding that low-frequency words have higher hit rates and lower false alarm rates than high-frequency words. This result is typically interpreted in terms of conventional signal detection theory (SDT), in which case it indicates that the order of the underlying old item distributions mirrors the order of the new item distributions. However, when viewed in terms of a mixture version of SDT, the order of hits and false alarms does not necessarily imply the same order in the underlying distributions because of possible effects of mixing. A reversal in underlying distributions did not appear for fits of mixture SDT models to data from 4 experiments.

Attention↗

PubMed2006

The influence of trial-to-trial recalibration on sequential effects in cross-modality matching.

Sequential effects are examined in a cross-modality matching experiment where observers adjusted the loudness of a tone in response to presented lengths of a metal tape. In one condition, the initial level of the tone to be adjusted was the same as the final adjusted level of the previous trial, whereas in another condition, the tone to be adjusted was reset to a different level before each trial. A fit of the DeCarlo-Cross dynamic model shows that the primary effect of the manipulation was on a judgmental factor, with little or no effect on a perceptual factor. We suggest that starting a trial with the tone at the final adjusted level of the previous trial induced the observer to rely more heavily on the loudness-length pair of the previous trial as a frame of reference for relative judgment; we call this reliance trial-to-trial recalibration. In contrast, when the tone is set to a level independent of its value on the previous trial, there is virtually no effect of one trial on the next trial's performance, a result consistent with the observer maintaining a stable frame of reference. We argue that sequential effects are not unavoidable and that the technique described here adds to a growing list of methods for reducing or eliminating them.

Association↗

PubMed2006

Telephone outreach to increase colorectal cancer screening in an urban minority population.

OBJECTIVES: We compared the effectiveness of a telephone outreach approach versus a direct mail approach in improving rates of colorectal cancer (CRC) screening in a predominantly Black population. METHODS: A randomized trial was conducted between 2000 and 2003 that followed 456 participants in the New York metropolitan area who had not had recent CRC screening. The intervention group received tailored telephone outreach, and the control group received mailed printed materials. The primary outcome was medically documented CRC screening 6 months or less after randomization. RESULTS: CRC screening was documented in 61 of 226 (27.0%) intervention participants and in 14 of 230 (6.1%) controls (prevalence rate difference=20.9%; 95% CI = 14.34, 27.46). Compared with the control group, the intervention group was 4.4 times more likely to receive CRC screening within 6 months of randomization. CONCLUSIONS: Tailored telephone outreach can increase CRC screening in an urban minority population.

Black or African American↗

PubMed2006

Sequential effects in successive ratio estimation.

Sequential effects are examined in four successive ratio estimation (RE) experiments. The procedure in successive RE is identical to that for magnitude estimation (ME), but the task in successive RE is to estimate the ratio of the current to the previous sensation magnitude, and not the separate magnitudes of the sensations. A positive stimulus context effect was found in successive RE for several continua, in agreement with results previously found for ME. The residual autocorrelation for successive RE was zero in many cases, but in some cases negative autocorrelation was found, which is in contrast to the positive autocorrelation that is typically found for ME and other magnitude scaling procedures. It is shown that, when the role of perceptual error is recognized, negative autocorrelation is predicted by a classical model of ratio estimation. Some aspects of response bias are also discussed.

Humans↗

PubMed2005

On bias in magnitude scaling and some conjectures of Stevens.

Bias in magnitude scaling can be viewed as involving deviations of judgments from proportionality. A model of bias is shown to provide a theoretical basis for Stevens's conjecture about geometrically averaging magnitude estimation and magnitude production exponents in order to obtain an estimate of the psychophysical exponent. An overlooked result is that one can also obtain an estimate of the magnitude of the bias. Examples from several well-known studies are presented. The bias is also shown to vary in response to experimental manipulation of the stimulus range. Aspects of predicting exponents across experiments are clarified, and a new prediction is examined. The model of bias fills some theoretical gaps in magnitude scaling and clarifies underlying assumptions and predictions.

Bias↗

PubMed2003

An application of signal detection theory with finite mixture distributions to source discrimination.

A mixture extension of signal detection theory is applied to source discrimination. The basic idea of the approach is that only a portion of the sources (say A or B) of items to be discriminated is encoded or attended to during the study period. As a result, in addition to 2 underlying probability distributions associated with the 2 sources, there is a 3rd distribution that represents items for which sources were not attended to. Thus, over trials, the observed response results from a mixture of an attended (A or B) distribution and a nonattended distribution. The situation differs in an interesting way from detection in that, for detection, there is mixing only on signal trials and not on noise trials, whereas for discrimination, there is mixing on both A and B trials. Predictions of the mixture model are examined for data from several recent studies and in a new experiment.

Association Learning↗

PubMed2003

An application of a dynamic model of judgment to magnitude production.

A dynamic model of judgment, together with a model of stimulus context effects, is applied to magnitude production (MP) and magnitude estimation (ME) experiments. Participants' responses in MP were correlated across trials, as is typically found for ME. The magnitudeof the autocorrelation, however, was small, which suggests that participants in MP tend to rely more heavily on a long-term frame of reference. Second, a stimulus context effect found for ME did not appear for MP, most likely because of the different nature of the task (i.e., intermediate values of the stimulus were heard while the participant produced a response). A fit of an earlier regression model, on the other hand, suggests that the number presented on the previous trial in MP has a large contrastive effect on the current response. The present model offers a different view of this result, in that it shows that a negative coefficient for the earlier model is consistent with a positive judgmental effect. The regression effect noted by Stevens and Greenbaum (1966), which is a value of the estimated ME exponent that is smaller than the inverse of the estimated MP exponent, was also found; it i s shown that the effect did not arise from bias in estimation.

Humans↗

PubMed2003

Using the PLUM procedure of SPSS to fit unequal variance and generalized signal detection models.

The recent addition of aprocedure in SPSS for the analysis of ordinal regression models offers a simple means for researchers to fit the unequal variance normal signal detection model and other extended signal detection models. The present article shows how to implement the analysis and how to interpret the SPSS output. Examples of fitting the unequal variance normal model and other generalized signal detection models are given. The approach offers a convenient means for applying signal detection theory to a variety of research.

Algorithms↗

PubMed2002

Regularities of source recognition: ROC analysis.

Source memory has become the focus of a growing number of investigations in a variety of fields. An appropriate model for source memory is, therefore, of increasing importance. A simple 2-dimensional signal-detection model of source recognition is presented. The receiver operating characteristics (ROCs) obtained from 3 experiments are then used to test the model. The data demonstrate 3 regularities: convex ROCs, z-ROCs with linear slopes of 1.00, and slightly concave z-ROCs. Two of these regularities support the model. The 3rd requires a revision of the model. This revised model is fitted to the data. The implications of these regularities for other theories are also discussed.

Adolescent↗

PubMed2002

Signal detection theory with finite mixture distributions: theoretical developments with applications to recognition memory.

An extension of signal detection theory (SDT) that incorporates mixtures of the underlying distributions is presented. The mixtures can be motivated by the idea that a presentation of a signal shifts the location of an underlying distribution only if the observer is attending to the signal; otherwise, the distribution is not shifted or is only partially shifted. Thus, trials with a signal presentation consist of a mixture of 2 (or more) latent classes of trials. Mixture SDT provides a general theoretical framework that offers a new perspective on a number of findings. For example, mixture SDT offers an alternative to the unequal variance signal detection model; it can also account for nonlinear normal receiver operating characteristic curves, as found in recent research.

Humans↗