Type2 _SDT _SSE.m (requires fit_meta_d_SSE.m) See the comments in the help section for full details. This function estimates meta-d' using response-conditional type 2 HRs and FARs and the empirical type 1 criterion c' as input. Minimizing sum of squared errors fit _meta _d _SSE.m This function uses an MLE method to fit the parameters of an unequal variance SDT model to behavioral data. This function handles different kinds of input formats, applies corrections to data to account for missing data cells, and calls the function SDT_MLE_fit to get an MLE estimate of the SDT parameter s for use with fit_meta_d_MLE. This is a wrap-around function you can use with fit_meta_d_MLE. Type2 _SDT _MLE.m (requires fit_meta_d_MLE.m and SDT_MLE_fit.m) More information on methodology coming soon. meta-d' computed separately for "S1" and "S2" responses. This function estimate response-specific meta-d', i.e. It takes as input a count of the number of times the subject used each available response for each stimulus type, as well as an estimate of the SDT parameter s. This function estimates meta-da as well as basic type 1 SDT parameters. Maximum likelihood estimation (MLE) - requires optimization toolbox However, they require use of Matlab's optimization toolbox. The MLE functions are also considerably faster. MLE methods are desirable for estimating the SDT parameter s, since least-squares methods ignore the variance in FAR data. One set uses maximum likelihood estimation (MLE), and the other works by minimizing the sum of squared errors. If you use the analysis files below, please reference the Consciousness & Cognition paper and this website.īrian _at_ psych -dot- columbia -dot- eduīelow are two sets of functions for conducting type 2 SDT analysis. doi:10.1016/j.concog.2011.09.021Ī more comprehensive treatment of conceptual, computational, and empirical issues regarding the method is available as an unpublished manuscript here. A signal detection theoretic approach for estimating metacognitive sensitivity from confidence ratings. A central idea is that primary task performance can influence metacognitive sensitivity, and it is informative to take this influence into account.ĭescription of the methodology can be found here: the efficacy with which confidence ratings discriminate between correct and incorrect judgments) in a signal detection theory framework. This analysis is intended to quantify metacognitive sensitivity (i.e. Type 2 signal detection theory analysis MATLAB files for conducting type 2 signal detection theory analysis
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