WSRt, critical thinking, a list of terms used in the articles of block 4

This is a list of the important terms used in the articles of the fourth block of WSRt, with the subject alternative approaches to psychological research.

Article: Kinds versus continua: a review of psychometric approaches to uncover the structure of psychiatric constructs

Equivalence classes: sets of individuals who are exchangeable with respect to the attribute of interest.

Taxometrics: by inspecting particular consequences of the model for specific statistical properties of (subsets of) items, such as the patterns of bivariate correlations expected to hold in the data

Toward a Model-Based Approach to the Clinical Assessment of Personality Psychopathology

Latent trait models: posit the presence of one or more underlying continuous distributions.

Zones of rarity: locations along the dimension that are unoccupied by some individuals.

Discrimination: the measure of how strongly the item taps into the latent trait.

Quasi-continuous: the construct would be bounded at the low end by zero, a complete absence of the quality corresponding with the construct.

Latent class models: based on the supposition of a latent group (class) structure for a construct’s distribution.

Conditional independence: that inter-item correlations solely reflect class membership.

Hybrid models (of factor mixture models): combine the continuous aspects of latent trait models with the discrete aspects of latent class models.

EFMA: exploratory factor mixture analysis.

Bayes and the probability of hypotheses

Objective probability: a long-run relative frequency.

Subjective probability: the subjective degree of conviction in a hypothesis.

The likelihood principle: the notion that all the information relevant to inference contained in data is provided by the likelihood.

Probability density distribution: the distribution of if the dependent variable can be assumed to vary continuously

Credibility interval: the Bayesian equivalent of a confidence interval

The Bayes factor: the Bayesian equivalent of null hypothesis testing

Flat prior or uniform prior: you have no idea what the population value is likely to be

Bayesian Versus orthodox statistics: which side are you on?

Alpha: the error rate for false positives, the significance level

 Beta: the error rate for false negatives

Likelihood: the probability of obtaining the exact data given the hypothesis.

The likelihood principle: all information relevant to inference contained in data is provided by the likelihood.

The Bayes factor (B): the ratio of likelihoods.

Subjective probabilities: personal convictions in an opinion.

Confidence intervals: the set of population values that the data are consistent with.

Network Analysis: An Integrative Approach to the Structure of Psychopathology

Bridge symptoms: symptoms that are part of both disorders.

A giant component: a large group of nodes that are all connected to one another, either directly or via intermediary nodes

A small world in the network analysis literature: on average, paths from one node to another are short and there is a large degree of clustering

Clustering: the extent to which nodes tend to form a connected group

Extended psychopathology networks: a network in which the activation of one person’s symptom not only has produced other symptoms within his own system, but also in the system of another person.

Partial correlations: the correlations between pairs of symptoms that remain when all other symptoms are controlled for

Time-series data: one asks individuals to report on various aspects of their physiological and psychological well-being at least once a day for many consecutive days.

Introduction to qualitative psychological research

Epistemology: particular sets of assumptions about the bases or possibilities of knowledge.

Ontology: the assumptions we make about the nature of being, existence or reality.

Positivism: holds that the relationship between the world and our sense perception of the world is straightforward.

Empiricism: holds that our knowledge of the world must arise from the collection and categorization of our sense perceptions/observations of the world.

Hypothetico-deductivism: the aim of research is not to obtain evidence that supports a theory but rather to identify theoretical claims (hyptheses) that are false and ultimately theories that are false.

Deductive reasoning in research: reasoning begins with theories, which are refined into hypotheses, which are tested through observations of some sort, which leads to a confirmation or rejection of the hypotheses.

Realism: the assumption that reality exists independent of the observer.

Nomothetic research: approaches which seek generalizable findings that uncover laws to explain objective phenomena.

Idiographic research: approaches which seek to examine individual cases in detail to understand an outcome.

Phenomenological methods: focus on obtaining detailed descriptions of experience as understood by those who have that experience in order to discern its essence.

Inductive reasoning in research: reasoning that begins with data, which are examined in light of a study’s research questions.

Critical realist outlook: assumes that, while a reality exits independent of the observer, we cannot know that reality with certainty.

Relativist: stance in which ‘reality’ is seen as dependent on the ways we come to know it.

Interpretative framework: ones professional and personal investments in the research.

Speaking position: including theoretical commitments, personal understandings and personal experiences.

Reflexivity: the acknowledgement by the researcher of the role played by their interpretative framework or speaking position in creating their analytic account.

Mixed-methods approach: both qualitative and quantitative methods being used in the same research object

Pluralistic analysis: the value of applying different qualitative methods with different ontologies and epistemologies to a single data set.

Surrogate Science: The Idol of a Universal Method for Scientific Inference - summary of an article by Gigerenzer & Marewski

The alpha level: the long-term relative frequency of mistakenly rejecting hypothesis H0 if it is true, also known as Type I error rate.

The beta level: the long-term frequency of mistakenly rejecting H1 if it is true.

Surrogate science: the attempt to infer the quality of research using a single number or benchmark.

This is the replication fallacy: a significant p value does not specify the probability that the same result can be reproduced in another study.

Fishing expeditions: disguising hypothesis testing as hypothesis testing.