ltm: An R Package for Latent Variable Modeling and Item Response Theory Analyses

By Dimitrios Rizopoulos. 2006

1,053 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/f319498f05bd4f8169ad837bb026459fdae69a1d

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Citations in the corpus

The Basics of Item Response Theory Using R (2018, methodology): “Rather than using any of the existing R packages developed specifically for IRT—e.g., mirt (Chalmers, 2012), ltm (Rizopoulos, 2006)—the tutorials in this book require only those functions that are available in base R.”
Estimating the Multilevel Rasch Model: With the lme4 Package (2007, methodology): “are used to calibrate items such as WINSTEPS (Linacre 2006), BILOG-MG (Zimowski, Muraki, Mislevy, and Bock 2005), PARSCALE (Muraki and Bock 2005), or ltm (Rizopoloulos 2006) in R (R Development Core Team 2007), with each program using a different estimating algorithm such as joint maximum likelihood”
Measuring the formal independence of regulatory agencies (2012, methodology): “Similar discrimination parameters were obtained using marginal maximum likelihood as implemented in the ltm package (Rizopoulos 2006), and through normal factor analysis imputing missing values with the item mean, and taking the first unrotated factor.”
A Didactic Presentation of Snijders’s lz* Index of Person Fit With Emphasis on Response Model Selection and Ability Estimation (2012, methodology): “The R package ltm (Rizopoulos, 2006) was considered for such an item calibration.”
An IRT analysis of motive questionnaires: The Unified Motive Scales (2012, methodology): “The ltm package was used for model estimation (Rizopoulos, 2006).”
mirt: A Multidimensional Item Response Theory Package for the R Environment (2012, methodology): “Several R ( R Development Core Team 2012) packages can be used to ﬁt IRT models, such as: the ltm package (Rizopoulos 2006), which can handle the Rasch, general latent trait, three-parameter logistic, and graded response models; the eRm package (Mair and Hatzinger 2007), which can ﬁt the rating…”
Evaluating the Impact of Careless Responding on Aggregated-Scores: To Filter Unmotivated Examinees or Not? (2017, methodology): “Secondly, item and person parameters for the recoded data were estimated based on the modified-3PL model using marginal Maximum Likelihood estimation in the R ltm package (Rizopoulos, 2006; step 2).”
The estimation of item response models with the lmer function from the lme4 package in R (2011, methodology): “Examples of packages in R of this first type are eRm (Mair and Hatzinger 2007), mlirt (Fox 2007), ltm (Rizopoulos 2006).”
Variational Approximations for Generalized Linear Latent Variable Models (2017, unknown): “…(Huber et al., 2004), where we wrote our own code to compute the estimates (see supplementary material), 4) the ltm function in the R package ltm (Rizopoulos, 2006), which uses a hybrid algorithm combining EM and quasi-Newton optimization, with the integration performed using Gauss-Hermite…”
Developing an Instrument for Teacher Feedback : Using the Rasch Model to Explore Teachers' Development of Effective Teaching Strategies and Behaviors (2018, methodology): “The analysis was performed in R using the package ltm (Rizopoulos, 2006).”
Lextale_FR A Fast, Free, and Efficient Test to Measure Language Proficiency in French (2013, unknown): “In a second step, we ran an item response theory (IRT) analysis on the remaining 90 items (with the R package ltm; Rizopoulos, 2006).”
The Musicality of Non-Musicians: An Index for Assessing Musical Sophistication in the General Population (2014, methodology): “For the unconstrained GRM of each subscale, we inspected the plots of the item information curves, the total test information value, the individual item information values, the item discrimination parameters, and the distribution of overall scores for the subscale.”
Why does the Cognitive Reflection Test (sometimes) predict utilitarian moral judgment (and other things) (2015, methodology): “We also used the ltm package (Rizopoulos, 2006) to fit a Rasch model to the data, as we explain later.”
Bayesian Item Response Modeling in R with brms and Stan (2019, background): “These are eRm (Mair and Hatzinger 2007), ltm (Rizopoulos 2006), TAM (Robitzsch et al.”
Modeling Attitudes Toward Science: Development and Validation of the Credibility of Science Scale (2017, methodology): “We then used IRT methods to evaluate individual item and overall test functioning, leveraging the graded response model (GRM) framework as implemented in the ltm package for the R statistical computing environment (Rizopoulos, 2006).”
Working Memory and Dynamic Measures of Analogical Reasoning as Predictors of Children's Math and Reading Achievement (2014, methodology): “The gPCM estimates were computed for the aggregated dataset (N= 379) using the ltm package for R (Rizopoulos, 2006).”