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Introduction
Fundamental cognitive processes, SFT, Modelling, statistics education
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Publications
Publications (28)
Since its inception, Systems Factorial Technology (SFT; Townsend & Nozawa, 1995) has been used alongside many research paradigms to detect the characteristics underlying a cognitive process. Here, we show how thresholds variability in a coactive architecture can result in an ambiguous diagnosis even when all SFT assumptions are met. We implemented...
The study of mental processes is at the forefront of research in cognitive psychology. However, the abilityto identify the architectures responsible for specific behaviors is often quite difficult. To alleviate this difficulty, recentprogress in mathematical psychology has brought forth Systems Factorial Technology (SFT; Townsend and Nozawa, 1995)....
Characteristics of a population are often unknown. To estimate such characteristics, random sampling must be used. Sampling is the process by which a subgroup of a population is examined in order to infer the values of the population's true characteristics. Estimates based on samples are approximations of the population's true value; therefore, it...
A group distribution is a synthesis of a set of individual distributions. To be adequate, a method for creating group distributions should not introduce characteristics that are not present in the individual distributions and preserve those that are present. A method occasionally used is quantile averaging (sometimes called vincentizations), applie...
The Same-Different task presents two stimuli in close succession and participants must indicate whether they are completely identical or if there are any attributes that differ. While the task is simple, its results have proven difficult to explain. Notably, response times are characterized by a fast-same effect whereby Same responses are faster th...
The same-different task is a classic paradigm that requires participants to judge whether two successively presented stimuli are the same or different. While this task is simple, with results that have been replicated many times, response times (RTs) and accuracy for both same and different decisions remain difficult to model. The biggest obstacle...
GRD is a popular tool to genenrate random data on the fly. It is most useful in statistic classes where the students can generate with a single short syntax, or using a graphical interface, random data that differs on every run but yet can implement effect sizes, outliers, etc. With the new versions of SPSS (version 27 and above) which is now using...
Plotting the data of an experiment allows researchers to illustrate the main results of a study, show effect sizes, compare conditions, and guide interpretations. To achieve all this, it is necessary to show point estimates of the results and their precision using error bars. Often, and potentially unbeknownst to them, researchers use a type of err...
The diffusion model is useful for analyzing data from decision making experiments as it gives information about a dataset that regular statistical tests cannot, including: the rate of processing, the encoding and motor response times, and decision thresholds. The EZ diffusion model is a restricted version of the diffusion model with some parameter...
Statistics courses prove to be a common difficulty to many social sciences students. To address this problem, we developed a tool in the R programming language \parencite {R18} that can be used to easily and quickly generate data to be analysed. The Generator of Random Data or GRD, allows the user to build datasets according to any design type, bot...
Les statistiques sont une matière notoirement difficile à enseigner aux étudiants des sciences humaines. L’anxiété statistique, une forme d’anxiété bien documentée chez ces étudiants, est présente dès le début du cours et explique donc une partie des difficultés rencontrées par ces étudiants. Cependant, nous croyons que l’anxiété statistique est la...
Statistical analyses have grown immensely since the inception of
computational methods. However, many quantitative methods classes teach sampling and sub-sampling at a very abstract level despite the fact that, with the faster computers of today, these notions could be demonstrated live to the students. For this reason, we have created a simple ex...
Pour effectuer des tâches simples, comme reconnaître les lettres d’un mot, le cerveau utilise plusieurs mécanismes. Ces mécanismes (ou sous-processus) travaillent de concert afin de générer une réponse adéquate (e.g., identifier la lettre « a »). Afin de mieux comprendre ce processus, il est pertinent d’enquêter sur les relations qui existent entre...
Afin de publier des résultats qui sont de plus en plus impressionnants, les scientifiques ont recours à des méthodes de recherche et des analyses qui sont devenues notamment plus complexes. Cependant, ceci fait en sorte que peu importe si ces résultats sont innovateurs ou non, ils sont presque impossibles à reproduire. En fait, les opportunités de...
The GRD extension command for SPSS (Harding & Cousineau, 2014) has been used in a variety of applications since its inception. Ranging from a teaching tool to demonstrate statistical analyses, to an inferential tool used to find critical values instead of looking into a z-table, GRD has been very well received. However, some users have requested ot...
Systems Factorial Technology (SFT) is a methodology capable of discerning five types of architectures involving two sub-processes. While reliable, SFT can wrongfully identify architectures (Tremblay et al., 2014). Here we explore the Linear Ballistic Accumulator (LBA; Brown & Heathcote, 2008), a sequential sampling model, embedded within a coactive...
The Pearson skew is a measure of asymmetry of a distribution, based on the difference between the mean and the median of a distribution. Here we show how to calculate the Pearson skew, estimate its standard error and the confidence interval. The derivation is based on a population following a normal distribution. Simulations explored the validity o...
To master statistics and data analysis tools, it is necessary to understand a number of concepts, manyof which are quite abstract. For example, sampling from a theoretical distribution can help individuals explore andunderstand randomness. Sampling can also be used to build exercises aimed to help students master statistics. Here, we present GRD (G...
System Factorial Technology is a recent methodology for the analysis of information processing architectures. SFT can discriminate between three processing architectures, namely serial, parallel and coactive processing. In addition , it can discriminate between two stopping rules, self-terminating and exhaustive. Although the previously stated arch...
Qu’est-ce que l’échantillon représente? Est-ce une copie de la population ou bien des données complètement différentes. Si une population a une moyenne de 100, est-ce que l’échantillon aura la même moyenne? Les concepts d’échantillonnage et de données aléatoires peuvent être très élusifs pour des nouveaux étudiants en statistiques. Cependant, même...
Les statistiques sont souvent une source d’anxiété chez les étudiants et de plus en plus les programmes de psychologie exigent qu’ils en acquièrent une expertise rapidement. Outre l’anxiété, il y a peut-être des concepts mal compris chez ceux-ci qui les empêchent d’apprendre rapidement. Parmi ces prérequis, un en particulier est mal compris: le con...
L’étude des processus mentaux est centrale pour la recherche en sciences cognitives. Cependant, il est difficile d’obtenir de l’information permettant de déterminer l’architecture interne et le fonctionnement de ces processus mentaux. Le System Factorial Technology est un outil d’analyse permettant de déterminer l’architecture interne, c’est-à-dire...
The same-different task is a simple task which demands the participant to judge whether two stimuli presented on screen are the same or different on their relevant dimensions. The task in itself is quite simple, and the ”same” responses are typically the fastest, an effect termed the fast-same phenomenon. However, models that attempt to explain the...
Coactivation is a model invoked to explain the improvement in performance (faster response time with similar amount of errors) when targets defined by redundant attributes are presented to observers. This model posits the existence of detectors for the individual attributes but, contrary to the statistical facilitation model, further assumes that t...
