A  B  C  D  E  F  G  H  I  J  K  L  M  N  O  P  Q  R  S  T  U  V  W  X  Y  Z  

  First | 1 2 3 4 5        [Sort by number of followers]   [Restore default list]

  Subjects -> PSYCHOLOGY (Total: 983 journals)
Showing 601 - 174 of 174 Journals sorted alphabetically
Revista Colombiana de Psicología     Open Access  
Revista Costarricense de Psicología     Open Access  
Revista de Cultura Teológica     Open Access  
Revista de Estudios e Investigación en Psicología y Educación     Open Access  
Revista de Investigacion Psicologica     Open Access  
Revista de Psicodidáctica     Open Access  
Revista de Psicodidáctica (English ed.)     Hybrid Journal   (Followers: 5)
Revista de Psicologia     Open Access  
Revista de Psicología     Open Access  
Revista de Psicología : Segunda Epoca     Open Access  
Revista de Psicología del Trabajo y de las Organizaciones     Open Access  
Revista de Psicología Social, International Journal of Social Psychology     Hybrid Journal   (Followers: 6)
Revista Electrónica de Metodología Aplicada     Open Access  
Revista Laborativa     Open Access  
Revista Latinoamericana de Psicología     Open Access  
Revista Psicológica Herediana     Open Access   (Followers: 1)
Revista Wímb Lu     Open Access  
Revue de psychoéducation     Full-text available via subscription   (Followers: 2)
Revue Européenne de Psychologie Appliquée / European Review of Applied Psychology     Hybrid Journal   (Followers: 3)
Revue québécoise de psychologie     Full-text available via subscription   (Followers: 2)
Rivista Internazionale di Filosofia e Psicologia     Open Access  
Roeper Review     Hybrid Journal   (Followers: 3)
Rorschachiana     Hybrid Journal  
RUDN Journal of Psychology and Pedagogics     Open Access  
SA Journal of Industrial Psychology     Open Access   (Followers: 3)
Satir International Journal     Open Access  
Scandinavian Journal of Psychology     Hybrid Journal   (Followers: 14)
Scandinavian Journal of Sport and Exercise Psychology     Open Access   (Followers: 5)
Scandinavian Psychoanalytic Review     Hybrid Journal  
School Psychology Quarterly     Full-text available via subscription   (Followers: 8)
School Psychology Review     Hybrid Journal   (Followers: 2)
Scientonomy : Journal for the Science of Science     Open Access   (Followers: 1)
Seeing and Perceiving     Hybrid Journal   (Followers: 1)
Self and Identity     Hybrid Journal   (Followers: 23)
Sexual Abuse A Journal of Research and Treatment     Hybrid Journal   (Followers: 43)
Sexual Abuse in Australia and New Zealand     Full-text available via subscription   (Followers: 9)
Sexual Offending : Theory, Research, and Prevention     Open Access   (Followers: 4)
Simmel Studies     Full-text available via subscription  
Sleep Medicine     Hybrid Journal   (Followers: 22)
Sleep Medicine : X     Open Access   (Followers: 4)
Social Action : The Journal for Social Action in Counseling and Psychology     Free   (Followers: 3)
Social and Personality Psychology Compass     Hybrid Journal   (Followers: 19)
Social Behavior and Personality : An International Journal     Full-text available via subscription   (Followers: 14)
Social Cognition     Full-text available via subscription   (Followers: 20)
Social Inclusion     Open Access   (Followers: 3)
Social Issues and Policy Review     Hybrid Journal   (Followers: 10)
Social Psychological and Personality Science     Hybrid Journal   (Followers: 40)
Social Psychology     Hybrid Journal   (Followers: 33)
Social Psychology Quarterly     Full-text available via subscription   (Followers: 24)
Social Science Research     Hybrid Journal   (Followers: 31)
Society and Security Insights     Open Access   (Followers: 1)
Socio-analysis     Full-text available via subscription   (Followers: 3)
Socioaffective Neuroscience and Psychology     Open Access   (Followers: 3)
Somnologie - Schlafforschung und Schlafmedizin     Hybrid Journal   (Followers: 1)
South African Journal of Psychology     Hybrid Journal   (Followers: 3)
Spanish Journal of Psychology     Hybrid Journal  
SSM - Mental Health     Open Access   (Followers: 1)
Studia z Kognitywistyki i Filozofii Umysłu     Open Access  
Studies in Asian Social Science     Open Access  
SUCHT - Zeitschrift für Wissenschaft und Praxis / Journal of Addiction Research and Practice     Hybrid Journal   (Followers: 4)
Suma Psicologica     Open Access  
Tajdida : Jurnal Pemikiran dan Gerakan Muhammadiyah     Open Access  
Teaching of Psychology     Hybrid Journal   (Followers: 11)
Terapia Psicológica     Open Access   (Followers: 1)
Tesis Psicologica     Open Access  
TESTFÓRUM     Open Access  
The Arts in Psychotherapy     Hybrid Journal   (Followers: 8)
The Brown University Psychopharmacology Update     Hybrid Journal   (Followers: 2)
The Clinical Neuropsychologist     Hybrid Journal   (Followers: 13)
The International Journal of Psychoanalysis     Hybrid Journal   (Followers: 6)
The Journals of Gerontology : Series B : Psychological Sciences and Social Sciences     Hybrid Journal   (Followers: 21)
The Psychoanalytic Quarterly     Hybrid Journal   (Followers: 3)
The Sport Psychologist     Hybrid Journal   (Followers: 12)
Themenzentrierte Interaktion     Hybrid Journal  
Therapeutic Advances in Psychopharmacology     Open Access   (Followers: 4)
Therapeutic Communities : The International Journal of Therapeutic Communities     Hybrid Journal   (Followers: 17)
Thérapie familiale     Full-text available via subscription   (Followers: 6)
Thinking & Reasoning     Hybrid Journal   (Followers: 6)
Tobacco Use Insights     Open Access   (Followers: 5)
Torture Journal     Open Access   (Followers: 2)
Transactional Analysis Journal     Hybrid Journal  
Transportation Research Part F: Traffic Psychology and Behaviour     Hybrid Journal   (Followers: 24)
Trauma, Violence, & Abuse     Hybrid Journal   (Followers: 25)
Undecidable Unconscious : A Journal of Deconstruction and Psychoanalysis     Full-text available via subscription   (Followers: 1)
Universal Journal of Psychology     Open Access  
Unoesc & Ciência - ACHS     Open Access  
Vinculo - Revista do NESME     Open Access  
VIVESIANA     Open Access  
Voices : The Art and Science of Psychotherapy     Full-text available via subscription   (Followers: 1)
Wege zum Menschen : Zeitschrift für Seelsorge und Beratung, heilendes und soziales Handeln     Hybrid Journal  
Wellbeing, Space & Society     Open Access   (Followers: 3)
Western Undergraduate Psychology Journal     Open Access  
Wiley Interdisciplinary Reviews: Cognitive Science     Hybrid Journal   (Followers: 7)
Yaşam Becerileri Psikoloji Dergisi / Life Skills Journal of Psychology     Open Access   (Followers: 1)
Zeitschrift für Arbeits - und Organisationspsychologie A&O     Hybrid Journal   (Followers: 2)
Zeitschrift für Differentielle und Diagnostische Psychologie     Full-text available via subscription  
Zeitschrift für Erziehungswissenschaft     Hybrid Journal   (Followers: 8)
Zeitschrift für Gerontopsychologie und -psychiatrie     Full-text available via subscription   (Followers: 1)
Zeitschrift für Gesundheitspsychologie     Hybrid Journal   (Followers: 3)
Zeitschrift für Individualpsychologie     Hybrid Journal  
Zeitschrift für Kinder- und Jugendpsychiatrie und Psychotherapie     Hybrid Journal   (Followers: 1)
Zeitschrift für Klinische Psychologie und Psychotherapie     Hybrid Journal   (Followers: 2)
Zeitschrift für Neuropsychologie     Hybrid Journal   (Followers: 2)
Zeitschrift für Pädagogische Psychologie     Hybrid Journal   (Followers: 1)
Zeitschrift für Psychiatrie, Psychologie und Psychotherapie     Hybrid Journal   (Followers: 2)
Zeitschrift für Psychodrama und Soziometrie     Hybrid Journal   (Followers: 1)
Zeitschrift für Psychologie     Hybrid Journal   (Followers: 2)
Zeitschrift für Psychologie / Journal of Psychology     Hybrid Journal   (Followers: 1)
Zeitschrift für Psychosomatische Medizin und Psychotherapie     Hybrid Journal  
Zeitschrift für Sportpsychologie     Hybrid Journal   (Followers: 1)

  First | 1 2 3 4 5        [Sort by number of followers]   [Restore default list]

Similar Journals
Journal Cover
Psychometrika
Journal Prestige (SJR): 2.374
Citation Impact (citeScore): 2
Number of Followers: 10  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1860-0980 - ISSN (Online) 0033-3123
Published by Springer-Verlag Homepage  [2468 journals]
  • Comparing Functional Trend and Learning among Groups in Intensive Binary
           

    • Free pre-print version: Loading...

      Abstract: Abstract This paper presents a model specification for group comparisons regarding a functional trend over time within a trial and learning across a series of trials in intensive binary longitudinal eye-tracking data. The functional trend and learning effects are modeled using by-variable smooth functions. This model specification is formulated as a generalized additive mixed model, which allowed for the use of the freely available mgcv package (Wood in Package ‘mgcv.’ https://cran.r-project.org/web/packages/mgcv/mgcv.pdf, 2023) in R. The model specification was applied to intensive binary longitudinal eye-tracking data, where the questions of interest concern differences between individuals with and without brain injury in their real-time language comprehension and how this affects their learning over time. The results of the simulation study show that the model parameters are recovered well and the by-variable smooth functions are adequately predicted in the same condition as those found in the application.
      PubDate: 2024-07-17
       
  • A Note on Ising Network Analysis with Missing Data

    • Free pre-print version: Loading...

      Abstract: Abstract The Ising model has become a popular psychometric model for analyzing item response data. The statistical inference of the Ising model is typically carried out via a pseudo-likelihood, as the standard likelihood approach suffers from a high computational cost when there are many variables (i.e., items). Unfortunately, the presence of missing values can hinder the use of pseudo-likelihood, and a listwise deletion approach for missing data treatment may introduce a substantial bias into the estimation and sometimes yield misleading interpretations. This paper proposes a conditional Bayesian framework for Ising network analysis with missing data, which integrates a pseudo-likelihood approach with iterative data imputation. An asymptotic theory is established for the method. Furthermore, a computationally efficient Pólya–Gamma data augmentation procedure is proposed to streamline the sampling of model parameters. The method’s performance is shown through simulations and a real-world application to data on major depressive and generalized anxiety disorders from the National Epidemiological Survey on Alcohol and Related Conditions (NESARC).
      PubDate: 2024-07-06
       
  • New Paradigm of Identifiable General-response Cognitive Diagnostic Models:
           Beyond Categorical Data

    • Free pre-print version: Loading...

      Abstract: Abstract Cognitive diagnostic models (CDMs) are a popular family of discrete latent variable models that model students’ mastery or deficiency of multiple fine-grained skills. CDMs have been most widely used to model categorical item response data such as binary or polytomous responses. With advances in technology and the emergence of varying test formats in modern educational assessments, new response types, including continuous responses such as response times, and count-valued responses from tests with repetitive tasks or eye-tracking sensors, have also become available. Variants of CDMs have been proposed recently for modeling such responses. However, whether these extended CDMs are identifiable and estimable is entirely unknown. We propose a very general cognitive diagnostic modeling framework for arbitrary types of multivariate responses with minimal assumptions, and establish identifiability in this general setting. Surprisingly, we prove that our general-response CDMs are identifiable under \({\textbf{Q}}\) -matrix-based conditions similar to those for traditional categorical-response CDMs. Our conclusions set up a new paradigm of identifiable general-response CDMs. We propose an EM algorithm to efficiently estimate a broad class of exponential family-based general-response CDMs. We conduct simulation studies under various response types. The simulation results not only corroborate our identifiability theory, but also demonstrate the superior empirical performance of our estimation algorithms. We illustrate our methodology by applying it to a TIMSS 2019 response time dataset.
      PubDate: 2024-07-05
       
  • Adventitious Error and Its Implications for Testing Relations Between
           Variables and for Composite Measurement Outcomes

    • Free pre-print version: Loading...

      Abstract: Abstract Wu and Browne (Psychometrika 80(3):571–600, 2015. https://doi.org/10.1007/s11336-015-9451-3; henceforth W &B) introduced the notion of adventitious error to explicitly take into account approximate goodness of fit of covariance structure models (CSMs). Adventitious error supposes that observed covariance matrices are not directly sampled from a theoretical population covariance matrix but from an operational population covariance matrix. This operational matrix is randomly distorted from the theoretical matrix due to differences in study implementations. W &B showed how adventitious error is linked to the root mean square error of approximation (RMSEA) and how the standard errors (SEs) of parameter estimates are augmented. Our contribution is to consider adventitious error as a general phenomenon and to illustrate its consequences. Using simulations, we illustrate that its impact on SEs can be generalized to pairwise relations between variables beyond the CSM context. Using derivations, we conjecture that heterogeneity of effect sizes across studies and overestimation of statistical power can both be interpreted as stemming from adventitious error. We also show that adventitious error, if it occurs, has an impact on the uncertainty of composite measurement outcomes such as factor scores and summed scores. The results of a simulation study show that the impact on measurement uncertainty is rather small although larger for factor scores than for summed scores. Adventitious error is an assumption about the data generating mechanism; the notion offers a statistical framework for understanding a broad range of phenomena, including approximate fit, varying research findings, heterogeneity of effects, and overestimates of power.
      PubDate: 2024-07-04
       
  • Temporally Dynamic, Cohort-Varying Value-Added Models

    • Free pre-print version: Loading...

      Abstract: Abstract We aim to estimate school value-added dynamically in time. Our principal motivation for doing so is to establish school effectiveness persistence while taking into account the temporal dependence that typically exists in school performance from one year to the next. We propose two methods of incorporating temporal dependence in value-added models. In the first we model the random school effects that are commonly present in value-added models with an auto-regressive process. In the second approach, we incorporate dependence in value-added estimators by modeling the performance of one cohort based on the previous cohort’s performance. An identification analysis allows us to make explicit the meaning of the corresponding value-added indicators: based on these meanings, we show that each model is useful for monitoring specific aspects of school persistence. Furthermore, we carefully detail how value-added can be estimated over time. We show through simulations that ignoring temporal dependence when it exists results in diminished efficiency in value-added estimation while incorporating it results in improved estimation (even when temporal dependence is weak). Finally, we illustrate the methodology by considering two cohorts from Chile’s national standardized test in mathematics.
      PubDate: 2024-06-22
       
  • Ordinal Outcome State-Space Models for Intensive Longitudinal Data

    • Free pre-print version: Loading...

      Abstract: Abstract Intensive longitudinal (IL) data are increasingly prevalent in psychological science, coinciding with technological advancements that make it simple to deploy study designs such as daily diary and ecological momentary assessments. IL data are characterized by a rapid rate of data collection (1+ collections per day), over a period of time, allowing for the capture of the dynamics that underlie psychological and behavioral processes. One powerful framework for analyzing IL data is state-space modeling, where observed variables are considered measurements for underlying states (i.e., latent variables) that change together over time. However, state-space modeling has typically relied on continuous measurements, whereas psychological data often come in the form of ordinal measurements such as Likert scale items. In this manuscript, we develop a general estimation approach for state-space models with ordinal measurements, specifically focusing on a graded response model for Likert scale items. We evaluate the performance of our model and estimator against that of the commonly used “linear approximation” model, which treats ordinal measurements as though they are continuous. We find that our model resulted in unbiased estimates of the state dynamics, while the linear approximation resulted in strongly biased estimates of the state dynamics. Finally, we develop an approximate standard error, termed slice standard errors and show that these approximate standard errors are more liberal than true standard errors (i.e., smaller) at a consistent bias.
      PubDate: 2024-06-11
       
  • The InterModel Vigorish as a Lens for Understanding (and Quantifying) the
           Value of Item Response Models for Dichotomously Coded Items

    • Free pre-print version: Loading...

      Abstract: Abstract The deployment of statistical models—such as those used in item response theory—necessitates the use of indices that are informative about the degree to which a given model is appropriate for a specific data context. We introduce the InterModel Vigorish (IMV) as an index that can be used to quantify accuracy for models of dichotomous item responses based on the improvement across two sets of predictions (i.e., predictions from two item response models or predictions from a single such model relative to prediction based on the mean). This index has a range of desirable features: It can be used for the comparison of non-nested models and its values are highly portable and generalizable. We use this fact to compare predictive performance across a variety of simulated data contexts and also demonstrate qualitative differences in behavior between the IMV and other common indices (e.g., the AIC and RMSEA). We also illustrate the utility of the IMV in empirical applications with data from 89 dichotomous item response datasets. These empirical applications help illustrate how the IMV can be used in practice and substantiate our claims regarding various aspects of model performance. These findings indicate that the IMV may be a useful indicator in psychometrics, especially as it allows for easy comparison of predictions across a variety of contexts.
      PubDate: 2024-06-03
       
  • Exploratory Procedure for Component-Based Structural Equation Modeling for
           Simple Structure by Simultaneous Rotation

    • Free pre-print version: Loading...

      Abstract: Abstract Generalized structured component analysis (GSCA) is a structural equation modeling (SEM) procedure that constructs components by weighted sums of observed variables and confirmatorily examines their regressional relationship. The research proposes an exploratory version of GSCA, called exploratory GSCA (EGSCA). EGSCA is analogous to exploratory SEM (ESEM) developed as an exploratory factor-based SEM procedure, which seeks the relationships between the observed variables and the components by orthogonal rotation of the parameter matrices. The indeterminacy of orthogonal rotation in GSCA is first shown as a theoretical support of the proposed method. The whole EGSCA procedure is then presented, together with a new rotational algorithm specialized to EGSCA, which aims at simultaneous simplification of all parameter matrices. Two numerical simulation studies revealed that EGSCA with the following rotation successfully recovered the true values of the parameter matrices and was superior to the existing GSCA procedure. EGSCA was applied to two real datasets, and the model suggested by the EGSCA’s result was shown to be better than the model proposed by previous research, which demonstrates the effectiveness of EGSCA in model exploration.
      PubDate: 2024-06-01
       
  • Measures of Agreement with Multiple Raters: Fréchet Variances and
           Inference

    • Free pre-print version: Loading...

      Abstract: Abstract Most measures of agreement are chance-corrected. They differ in three dimensions: their definition of chance agreement, their choice of disagreement function, and how they handle multiple raters. Chance agreement is usually defined in a pairwise manner, following either Cohen’s kappa or Fleiss’s kappa. The disagreement function is usually a nominal, quadratic, or absolute value function. But how to handle multiple raters is contentious, with the main contenders being Fleiss’s kappa, Conger’s kappa, and Hubert’s kappa, the variant of Fleiss’s kappa where agreement is said to occur only if every rater agrees. More generally, multi-rater agreement coefficients can be defined in a g-wise way, where the disagreement weighting function uses g raters instead of two. This paper contains two main contributions. (a) We propose using Fréchet variances to handle the case of multiple raters. The Fréchet variances are intuitive disagreement measures and turn out to generalize the nominal, quadratic, and absolute value functions to the case of more than two raters. (b) We derive the limit theory of g-wise weighted agreement coefficients, with chance agreement of the Cohen-type or Fleiss-type, for the case where every item is rated by the same number of raters. Trying out three confidence interval constructions, we end up recommending calculating confidence intervals using the arcsine transform or the Fisher transform.
      PubDate: 2024-06-01
       
  • On the Identifiability of 3- and 4-Parameter Item Response Theory Models
           From the Perspective of Knowledge Space Theory

    • Free pre-print version: Loading...

      Abstract: Abstract The present work aims at showing that the identification problems (here meant as both issues of empirical indistinguishability and unidentifiability) of some item response theory models are related to the notion of identifiability in knowledge space theory. Specifically, that the identification problems of the 3- and 4-parameter models are related to the more general issues of forward- and backward-gradedness in all items of the power set, which is the knowledge structure associated with IRT models under the assumption of local independence. As a consequence, the identifiability problem of a 4-parameter model is split into two parts: a first one, which is the result of a trade-off between the left-side added parameters and the remainder of the Item Response Function, e.g., a 2-parameter model, and a second one, which is the already well-known identifiability issue of the 2-parameter model itself. Application of the results to the logistic case appears to provide both a confirmation and a generalization of the current findings in the literature for both fixed- and random-effects IRT logistic models.
      PubDate: 2024-06-01
       
  • Restricted Latent Class Models for Nominal Response Data: Identifiability
           and Estimation

    • Free pre-print version: Loading...

      Abstract: Abstract Restricted latent class models (RLCMs) provide an important framework for diagnosing and classifying respondents on a collection of multivariate binary responses. Recent research made significant advances in theory for establishing identifiability conditions for RLCMs with binary and polytomous response data. Multiclass data, which are unordered nominal response data, are also widely collected in the social sciences and psychometrics via forced-choice inventories and multiple choice tests. We establish new identifiability conditions for parameters of RLCMs for multiclass data and discuss the implications for substantive applications. The new identifiability conditions are applicable to a wealth of RLCMs for polytomous and nominal response data. We propose a Bayesian framework for inferring model parameters, assess parameter recovery in a Monte Carlo simulation study, and present an application of the model to a real dataset.
      PubDate: 2024-06-01
       
  • What Can We Learn from a Semiparametric Factor Analysis of Item Responses
           and Response Time' An Illustration with the PISA 2015 Data

    • Free pre-print version: Loading...

      Abstract: Abstract It is widely believed that a joint factor analysis of item responses and response time (RT) may yield more precise ability scores that are conventionally predicted from responses only. For this purpose, a simple-structure factor model is often preferred as it only requires specifying an additional measurement model for item-level RT while leaving the original item response theory (IRT) model for responses intact. The added speed factor indicated by item-level RT correlates with the ability factor in the IRT model, allowing RT data to carry additional information about respondents’ ability. However, parametric simple-structure factor models are often restrictive and fit poorly to empirical data, which prompts under-confidence in the suitablity of a simple factor structure. In the present paper, we analyze the 2015 Programme for International Student Assessment mathematics data using a semiparametric simple-structure model. We conclude that a simple factor structure attains a decent fit after further parametric assumptions in the measurement model are sufficiently relaxed. Furthermore, our semiparametric model implies that the association between latent ability and speed/slowness is strong in the population, but the form of association is nonlinear. It follows that scoring based on the fitted model can substantially improve the precision of ability scores.
      PubDate: 2024-06-01
       
  • Using External Information for More Precise Inferences in General
           Regression Models

    • Free pre-print version: Loading...

      Abstract: Abstract Empirical research usually takes place in a space of available external information, like results from single studies, meta-analyses, official statistics or subjective (expert) knowledge. The available information ranges from simple means and proportions to known relations between a multitude of variables or estimated distributions. In psychological research, external information derived from the named sources may be used to build a theory and derive hypotheses. In addition, techniques do exist that use external information in the estimation process, for example prior distributions in Bayesian statistics. In this paper, we discuss the benefits of adopting generalized method of moments with external moments, as another example for such a technique. Analytical formulas for estimators and their variances in the multiple linear regression case are derived. An R function that implements these formulas is provided in the supplementary material for general applied use. The effects of various practically relevant moments are analyzed and tested in a simulation study. A new approach to robustify the estimators against misspecification of the external moments based on the concept of imprecise probabilities is introduced. Finally, the resulting externally informed model is applied to a dataset to investigate the predictability of the premorbid intelligence quotient based on lexical tasks, leading to a reduction of variances and thus to narrower confidence intervals.
      PubDate: 2024-06-01
       
  • A Spectral Method for Identifiable Grade of Membership Analysis with
           Binary Responses

    • Free pre-print version: Loading...

      Abstract: Abstract Grade of membership (GoM) models are popular individual-level mixture models for multivariate categorical data. GoM allows each subject to have mixed memberships in multiple extreme latent profiles. Therefore, GoM models have a richer modeling capacity than latent class models that restrict each subject to belong to a single profile. The flexibility of GoM comes at the cost of more challenging identifiability and estimation problems. In this work, we propose a singular value decomposition (SVD)-based spectral approach to GoM analysis with multivariate binary responses. Our approach hinges on the observation that the expectation of the data matrix has a low-rank decomposition under a GoM model. For identifiability, we develop sufficient and almost necessary conditions for a notion of expectation identifiability. For estimation, we extract only a few leading singular vectors of the observed data matrix and exploit the simplex geometry of these vectors to estimate the mixed membership scores and other parameters. We also establish the consistency of our estimator in the double-asymptotic regime where both the number of subjects and the number of items grow to infinity. Our spectral method has a huge computational advantage over Bayesian or likelihood-based methods and is scalable to large-scale and high-dimensional data. Extensive simulation studies demonstrate the superior efficiency and accuracy of our method. We also illustrate our method by applying it to a personality test dataset.
      PubDate: 2024-06-01
       
  • Remarks From the Editor-in-Chief

    • Free pre-print version: Loading...

      PubDate: 2024-05-31
       
  • Learning Bayesian Networks: A Copula Approach for Mixed-Type Data

    • Free pre-print version: Loading...

      Abstract: Abstract Estimating dependence relationships between variables is a crucial issue in many applied domains and in particular psychology. When several variables are entertained, these can be organized into a network which encodes their set of conditional dependence relations. Typically however, the underlying network structure is completely unknown or can be partially drawn only; accordingly it should be learned from the available data, a process known as structure learning. In addition, data arising from social and psychological studies are often of different types, as they can include categorical, discrete and continuous measurements. In this paper, we develop a novel Bayesian methodology for structure learning of directed networks which applies to mixed data, i.e., possibly containing continuous, discrete, ordinal and binary variables simultaneously. Whenever available, our method can easily incorporate known dependence structures among variables represented by paths or edge directions that can be postulated in advance based on the specific problem under consideration. We evaluate the proposed method through extensive simulation studies, with appreciable performances in comparison with current state-of-the-art alternative methods. Finally, we apply our methodology to well-being data from a social survey promoted by the United Nations, and mental health data collected from a cohort of medical students. R code implementing the proposed methodology is available at https://github.com/FedeCastelletti/bayes_networks_mixed_data.
      PubDate: 2024-04-12
      DOI: 10.1007/s11336-024-09969-2
       
  • Book Review

    • Free pre-print version: Loading...

      PubDate: 2024-04-03
      DOI: 10.1007/s11336-024-09958-5
       
  • Efficient Corrections for Standardized Person-Fit Statistics

    • Free pre-print version: Loading...

      Abstract: Abstract Many popular person-fit statistics belong to the class of standardized person-fit statistics, T, and are assumed to have a standard normal null distribution. However, in practice, this assumption is incorrect since T is computed using (a) an estimated ability parameter and (b) a finite number of items. Snijders (Psychometrika 66(3):331–342, 2001) developed mean and variance corrections for T to account for the use of an estimated ability parameter. Bedrick (Psychometrika 62(2):191–199, 1997) and Molenaar and Hoijtink (Psychometrika 55(1):75–106, 1990) developed skewness corrections for T to account for the use of a finite number of items. In this paper, we combine these two lines of research and propose three new corrections for T that simultaneously account for the use of an estimated ability parameter and the use of a finite number of items. The new corrections are efficient in that they only require the analysis of the original data set and do not require the simulation or analysis of any additional data sets. We conducted a detailed simulation study and found that the new corrections are able to control the Type I error rate while also maintaining reasonable levels of power. A real data example is also included.
      PubDate: 2024-04-01
      DOI: 10.1007/s11336-024-09960-x
       
  • A Model Implied Instrumental Variable Approach to Exploratory Factor
           Analysis (MIIV-EFA)

    • Free pre-print version: Loading...

      Abstract: Abstract Spearman (Am J Psychol 15(1):201–293, 1904. https://doi.org/10.2307/1412107) marks the birth of factor analysis. Many articles and books have extended his landmark paper in permitting multiple factors and determining the number of factors, developing ideas about simple structure and factor rotation, and distinguishing between confirmatory and exploratory factor analysis (CFA and EFA). We propose a new model implied instrumental variable (MIIV) approach to EFA that allows intercepts for the measurement equations, correlated common factors, correlated errors, standard errors of factor loadings and measurement intercepts, overidentification tests of equations, and a procedure for determining the number of factors. We also permit simpler structures by removing nonsignificant loadings. Simulations of factor analysis models with and without cross-loadings demonstrate the impressive performance of the MIIV-EFA procedure in recovering the correct number of factors and in recovering the primary and secondary loadings. For example, in nearly all replications MIIV-EFA finds the correct number of factors when N is 100 or more. Even the primary and secondary loadings of the most complex models were recovered when the sample sizes were at least 500. We discuss limitations and future research areas. Two appendices describe alternative MIIV-EFA algorithms and the sensitivity of the algorithm to cross-loadings.
      PubDate: 2024-03-26
      DOI: 10.1007/s11336-024-09949-6
       
  • Sufficient and Necessary Conditions for the Identifiability of DINA Models
           with Polytomous Responses

    • Free pre-print version: Loading...

      Abstract: Abstract Cognitive diagnosis models (CDMs) provide a powerful statistical and psychometric tool for researchers and practitioners to learn fine-grained diagnostic information about respondents’ latent attributes. There has been a growing interest in the use of CDMs for polytomous response data, as more and more items with multiple response options become widely used. Similar to many latent variable models, the identifiability of CDMs is critical for accurate parameter estimation and valid statistical inference. However, the existing identifiability results are primarily focused on binary response models and have not adequately addressed the identifiability of CDMs with polytomous responses. This paper addresses this gap by presenting sufficient and necessary conditions for the identifiability of the widely used DINA model with polytomous responses, with the aim to provide a comprehensive understanding of the identifiability of CDMs with polytomous responses and to inform future research in this field.
      PubDate: 2024-03-22
      DOI: 10.1007/s11336-024-09961-w
       
 
JournalTOCs
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
Tel: +00 44 (0)131 4513762
 


Your IP address: 44.211.31.134
 
Home (Search)
API
About JournalTOCs
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-
JournalTOCs
 
 

 A  B  C  D  E  F  G  H  I  J  K  L  M  N  O  P  Q  R  S  T  U  V  W  X  Y  Z  

  First | 1 2 3 4 5        [Sort by number of followers]   [Restore default list]

  Subjects -> PSYCHOLOGY (Total: 983 journals)
Showing 601 - 174 of 174 Journals sorted alphabetically
Revista Colombiana de Psicología     Open Access  
Revista Costarricense de Psicología     Open Access  
Revista de Cultura Teológica     Open Access  
Revista de Estudios e Investigación en Psicología y Educación     Open Access  
Revista de Investigacion Psicologica     Open Access  
Revista de Psicodidáctica     Open Access  
Revista de Psicodidáctica (English ed.)     Hybrid Journal   (Followers: 5)
Revista de Psicologia     Open Access  
Revista de Psicología     Open Access  
Revista de Psicología : Segunda Epoca     Open Access  
Revista de Psicología del Trabajo y de las Organizaciones     Open Access  
Revista de Psicología Social, International Journal of Social Psychology     Hybrid Journal   (Followers: 6)
Revista Electrónica de Metodología Aplicada     Open Access  
Revista Laborativa     Open Access  
Revista Latinoamericana de Psicología     Open Access  
Revista Psicológica Herediana     Open Access   (Followers: 1)
Revista Wímb Lu     Open Access  
Revue de psychoéducation     Full-text available via subscription   (Followers: 2)
Revue Européenne de Psychologie Appliquée / European Review of Applied Psychology     Hybrid Journal   (Followers: 3)
Revue québécoise de psychologie     Full-text available via subscription   (Followers: 2)
Rivista Internazionale di Filosofia e Psicologia     Open Access  
Roeper Review     Hybrid Journal   (Followers: 3)
Rorschachiana     Hybrid Journal  
RUDN Journal of Psychology and Pedagogics     Open Access  
SA Journal of Industrial Psychology     Open Access   (Followers: 3)
Satir International Journal     Open Access  
Scandinavian Journal of Psychology     Hybrid Journal   (Followers: 14)
Scandinavian Journal of Sport and Exercise Psychology     Open Access   (Followers: 5)
Scandinavian Psychoanalytic Review     Hybrid Journal  
School Psychology Quarterly     Full-text available via subscription   (Followers: 8)
School Psychology Review     Hybrid Journal   (Followers: 2)
Scientonomy : Journal for the Science of Science     Open Access   (Followers: 1)
Seeing and Perceiving     Hybrid Journal   (Followers: 1)
Self and Identity     Hybrid Journal   (Followers: 23)
Sexual Abuse A Journal of Research and Treatment     Hybrid Journal   (Followers: 43)
Sexual Abuse in Australia and New Zealand     Full-text available via subscription   (Followers: 9)
Sexual Offending : Theory, Research, and Prevention     Open Access   (Followers: 4)
Simmel Studies     Full-text available via subscription  
Sleep Medicine     Hybrid Journal   (Followers: 22)
Sleep Medicine : X     Open Access   (Followers: 4)
Social Action : The Journal for Social Action in Counseling and Psychology     Free   (Followers: 3)
Social and Personality Psychology Compass     Hybrid Journal   (Followers: 19)
Social Behavior and Personality : An International Journal     Full-text available via subscription   (Followers: 14)
Social Cognition     Full-text available via subscription   (Followers: 20)
Social Inclusion     Open Access   (Followers: 3)
Social Issues and Policy Review     Hybrid Journal   (Followers: 10)
Social Psychological and Personality Science     Hybrid Journal   (Followers: 40)
Social Psychology     Hybrid Journal   (Followers: 33)
Social Psychology Quarterly     Full-text available via subscription   (Followers: 24)
Social Science Research     Hybrid Journal   (Followers: 31)
Society and Security Insights     Open Access   (Followers: 1)
Socio-analysis     Full-text available via subscription   (Followers: 3)
Socioaffective Neuroscience and Psychology     Open Access   (Followers: 3)
Somnologie - Schlafforschung und Schlafmedizin     Hybrid Journal   (Followers: 1)
South African Journal of Psychology     Hybrid Journal   (Followers: 3)
Spanish Journal of Psychology     Hybrid Journal  
SSM - Mental Health     Open Access   (Followers: 1)
Studia z Kognitywistyki i Filozofii Umysłu     Open Access  
Studies in Asian Social Science     Open Access  
SUCHT - Zeitschrift für Wissenschaft und Praxis / Journal of Addiction Research and Practice     Hybrid Journal   (Followers: 4)
Suma Psicologica     Open Access  
Tajdida : Jurnal Pemikiran dan Gerakan Muhammadiyah     Open Access  
Teaching of Psychology     Hybrid Journal   (Followers: 11)
Terapia Psicológica     Open Access   (Followers: 1)
Tesis Psicologica     Open Access  
TESTFÓRUM     Open Access  
The Arts in Psychotherapy     Hybrid Journal   (Followers: 8)
The Brown University Psychopharmacology Update     Hybrid Journal   (Followers: 2)
The Clinical Neuropsychologist     Hybrid Journal   (Followers: 13)
The International Journal of Psychoanalysis     Hybrid Journal   (Followers: 6)
The Journals of Gerontology : Series B : Psychological Sciences and Social Sciences     Hybrid Journal   (Followers: 21)
The Psychoanalytic Quarterly     Hybrid Journal   (Followers: 3)
The Sport Psychologist     Hybrid Journal   (Followers: 12)
Themenzentrierte Interaktion     Hybrid Journal  
Therapeutic Advances in Psychopharmacology     Open Access   (Followers: 4)
Therapeutic Communities : The International Journal of Therapeutic Communities     Hybrid Journal   (Followers: 17)
Thérapie familiale     Full-text available via subscription   (Followers: 6)
Thinking & Reasoning     Hybrid Journal   (Followers: 6)
Tobacco Use Insights     Open Access   (Followers: 5)
Torture Journal     Open Access   (Followers: 2)
Transactional Analysis Journal     Hybrid Journal  
Transportation Research Part F: Traffic Psychology and Behaviour     Hybrid Journal   (Followers: 24)
Trauma, Violence, & Abuse     Hybrid Journal   (Followers: 25)
Undecidable Unconscious : A Journal of Deconstruction and Psychoanalysis     Full-text available via subscription   (Followers: 1)
Universal Journal of Psychology     Open Access  
Unoesc & Ciência - ACHS     Open Access  
Vinculo - Revista do NESME     Open Access  
VIVESIANA     Open Access  
Voices : The Art and Science of Psychotherapy     Full-text available via subscription   (Followers: 1)
Wege zum Menschen : Zeitschrift für Seelsorge und Beratung, heilendes und soziales Handeln     Hybrid Journal  
Wellbeing, Space & Society     Open Access   (Followers: 3)
Western Undergraduate Psychology Journal     Open Access  
Wiley Interdisciplinary Reviews: Cognitive Science     Hybrid Journal   (Followers: 7)
Yaşam Becerileri Psikoloji Dergisi / Life Skills Journal of Psychology     Open Access   (Followers: 1)
Zeitschrift für Arbeits - und Organisationspsychologie A&O     Hybrid Journal   (Followers: 2)
Zeitschrift für Differentielle und Diagnostische Psychologie     Full-text available via subscription  
Zeitschrift für Erziehungswissenschaft     Hybrid Journal   (Followers: 8)
Zeitschrift für Gerontopsychologie und -psychiatrie     Full-text available via subscription   (Followers: 1)
Zeitschrift für Gesundheitspsychologie     Hybrid Journal   (Followers: 3)
Zeitschrift für Individualpsychologie     Hybrid Journal  
Zeitschrift für Kinder- und Jugendpsychiatrie und Psychotherapie     Hybrid Journal   (Followers: 1)
Zeitschrift für Klinische Psychologie und Psychotherapie     Hybrid Journal   (Followers: 2)
Zeitschrift für Neuropsychologie     Hybrid Journal   (Followers: 2)
Zeitschrift für Pädagogische Psychologie     Hybrid Journal   (Followers: 1)
Zeitschrift für Psychiatrie, Psychologie und Psychotherapie     Hybrid Journal   (Followers: 2)
Zeitschrift für Psychodrama und Soziometrie     Hybrid Journal   (Followers: 1)
Zeitschrift für Psychologie     Hybrid Journal   (Followers: 2)
Zeitschrift für Psychologie / Journal of Psychology     Hybrid Journal   (Followers: 1)
Zeitschrift für Psychosomatische Medizin und Psychotherapie     Hybrid Journal  
Zeitschrift für Sportpsychologie     Hybrid Journal   (Followers: 1)

  First | 1 2 3 4 5        [Sort by number of followers]   [Restore default list]

Similar Journals
Similar Journals
HOME > Browse the 73 Subjects covered by JournalTOCs  
SubjectTotal Journals
 
 
JournalTOCs
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
Tel: +00 44 (0)131 4513762
 


Your IP address: 44.211.31.134
 
Home (Search)
API
About JournalTOCs
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-