Relevant bibliographies by topics / Raven’s Progressive Matrices

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Raven’s Progressive Matrices'

Author: Grafiati
Published: 4 June 2021
Last updated: 8 February 2022

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Journal articles on the topic "Raven’s Progressive Matrices"

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Paul, Steven M. "The Advanced Raven’s Progressive Matrices." Journal of Experimental Education 54, no. 2 (January 1986): 95–100. http://dx.doi.org/10.1080/00220973.1986.10806404.

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van der Ven, A. H. G. S., and J. L. Ellis. "A Rasch analysis of Raven’s standard progressive matrices." Personality and Individual Differences 29, no. 1 (July 2000): 45–64. http://dx.doi.org/10.1016/s0191-8869(99)00177-4.

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Flynn, James R., and Lilia Rossi-Casé. "Modern women match men on Raven’s Progressive Matrices." Personality and Individual Differences 50, no. 6 (April 2011): 799–803. http://dx.doi.org/10.1016/j.paid.2010.12.035.

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Shibaev, Vladimir, Andrei Grigoriev, Ekaterina Valueva, and Anatoly Karlin. "Differential Item Functioning on Raven’s SPM+ Amongst Two Convenience Samples of Yakuts and Russians." Psych 2, no. 1 (January 9, 2020): 44–51. http://dx.doi.org/10.3390/psych2010005.

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National IQ estimates are based on psychometric measurements carried out in a variety of cultural contexts and are often obtained from Raven’s Progressive Matrices tests. In a series of studies, J. Philippe Rushton et al. have argued that these tests are not biased with respect to ethnicity or race. Critics claimed their methods were inappropriate and suggested differential item functioning (DIF) analysis as a more suitable alternative. In the present study, we conduct a DIF analysis on Raven’s Standard Progressive Matrices Plus (SPM+) tests administered to convenience samples of Yakuts and ethnic Russians. The Yakuts scored lower than the Russians by 4.8 IQ points, a difference that can be attributed to the selectiveness of the Russian sample. Data from the Yakut (n = 518) and Russian (n = 956) samples were analyzed for DIF using logistic regression. Although items B9, B10, B11, B12, and C11 were identified as having uniform DIF, all of these DIF effects can be regarded as negligible (R2 <0.13). This is consistent with Rushton et al.’s arguments that the Raven’s Progressive Matrices tests are ethnically unbiased.
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Raudies, Florian, and Michael E. Hasselmo. "A model of symbolic processing in Raven’s progressive matrices." Biologically Inspired Cognitive Architectures 21 (July 2017): 47–58. http://dx.doi.org/10.1016/j.bica.2017.07.003.

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Troncone, Alda, Antonietta Chianese, Angela Zanfardino, Crescenzo Cascella, Santino Confetto, Laura Perrone, and Dario Iafusco. "Nonverbal intelligence and scholastic performance in children with type 1 diabetes." Journal of Health Psychology 24, no. 2 (June 27, 2017): 229–39. http://dx.doi.org/10.1177/1359105317715093.

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This study examined nonverbal intelligence and scholastic achievement in children with type 1 diabetes. In a retrospective case–control study, 69 children (35 males) ages 5–10 years with type 1 diabetes and 69 healthy controls matched to patients by age, gender and socioeconomic status were compared according to their performance on Raven’s Coloured Progressive Matrices and their scholastic grades. No differences in nonverbal intelligence and grades were observed between children with type 1 diabetes and healthy control subjects. Raven’s Coloured Progressive Matrices scores inversely correlated with duration of illness both in children with early onset of type 1 diabetes and poor metabolic control. Possible explanations of the results and implications are discussed.
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Lúcio, Patrícia Silva, Hugo Cogo-Moreira, Marina Puglisi, Guilherme Vanoni Polanczyk, and Todd D. Little. "Psychometric Investigation of the Raven’s Colored Progressive Matrices Test in a Sample of Preschool Children." Assessment 26, no. 7 (November 9, 2017): 1399–408. http://dx.doi.org/10.1177/1073191117740205.

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The present study investigated the psychometric properties of the Raven’s Colored Progressive Matrices (CPM) test in a sample of preschoolers from Brazil ( n = 582; age: mean = 57 months, SD = 7 months; 46% female). We investigated the plausibility of unidimensionality of the items (confirmatory factor analysis) and differential item functioning (DIF) for sex and age (multiple indicators multiple causes method). We tested four unidimensional models and the one with the best-fit index was a reduced form of the Raven’s CPM. The DIF analysis was carried out with the reduced form of the test. A few items presented DIF (two for sex and one for age), confirming that the Raven’s CPM items are mostly measurement invariant. There was no effect of sex on the general factor, but increasing age was associated with higher values of the g factor. Future research should indicate if the reduced form is suitable for evaluating the general ability of preschoolers.
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Suwartono, Christiany, Cahyo Pratomo Amiseso, and Restu Tri Handoyo. "Uji Reliabilitas dan Validitas Eksternal The Raven’s Standard Progressive Matrices." HUMANITAS 14, no. 1 (February 1, 2017): 1. http://dx.doi.org/10.26555/humanitas.v14i1.5772.

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Waschl, N., T. Nettelbeck, S. Jackson, and N. Burns. "Seeing reason: The dimensionality of the Advanced Raven’s Progressive Matrices." Personality and Individual Differences 101 (October 2016): 525. http://dx.doi.org/10.1016/j.paid.2016.05.344.

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Salahodjaev, Raufhon, Bekhzod Omanbeyev, Meerim Karybava, Nurhazhan Bostonova, and Richard Lynn. "A Standardization of Raven’s Standard Progressive Matrices Test in Kyrgyzstan." Mankind Quarterly 57, no. 3 (2017): 443–47. http://dx.doi.org/10.46469/mq.2017.57.3.13.

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Dissertations / Theses on the topic "Raven’s Progressive Matrices"

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Dahlgren, Simon. "The association between cognition and speech-in-noise perception : Investigating the link between speech-in-noise perception and fluid intelligence in people with and without hearing loss." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-166708.

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The link between speech-in-noise recognition and cognition has been researched extensively over the years, and the purpose of this thesis was to add to this field. Data from a sample of 394 participants from the n200 database (Rönnberg et al., 2016) was used to calculate the correlation between their performance on a speech-in-noise test and their score on a test measuring fluid intelligence. The speech-in-noise test consisted of matrix sentences with 4-talker babble as noise and fluid intelligence was represented by the score on a Raven’s Progressive Matrices test. Around half of the participants (n = 199) had documented hearing loss and were hearing aid users, while the rest were participants with normal hearing. The overall correlation between speech-in-noise recognition and fluid intelligence was -.317, which shows that a better (lower) score on the speech-in-noise test is correlated to a better score in the Raven’s test. The same type of correlation was calculated within the two different groups, and the results showed correlation of -.338 for the group without hearing loss and one of -.303 for the group with hearing loss. The results indicate that there is a weak to moderate correlation between speech-in-noise and fluid intelligence, and they support the theory that cognitive processing is related to speech perception in all people, regardless of hearing status.
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Abdalgadr, Alsedig A. A. "Standardization of Raven's standard progressive matrices test for a Libyan sample." Thesis, University of Salford, 2009. http://usir.salford.ac.uk/26487/.

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Background: Until date, no IQ test has been standardized to be used to test the intelligence of Libyan students. Lack of standardized intelligence tests creates many problems such as the misuse of some non-standardised tests. These tests are carried out to estimate the mental ability of mentally retarded or gifted children. This problem prompted the researcher to study the SPM test which is considered by many researchers as one of the most used culturally-fair tests. The aim of this study was to standardize the SPM test to a Libyan setting to develop norms for the classic form of the SPM test to identify the distribution of IQ scores within Libyan students. Sample and methods: a total sample size of 2600 students (aged 8 to 21 years) was chosen using a multi-stage, cluster-disproportional stratified sampling method. During September and November 2007, the SPM test was administered to 1800 school students from 72 schools from 11 settlements (two cities and nine villages). In addition, during September and November 2008, the SPM test was administered to 800 university students from two different branches of Omar El-Mukhtar University located in two cities (Al-Baida and Al-Marj). Quantitative research designs (descriptive and comparative survey, correlational and cross-sectional) were used. In addition, a meta-analysis was performed to compare SPM test results with studies carried out in other countries. Data collected were imported into (SPSS) (version 16)software. Normality testing was carried out, the collected data were normally distributed which warranted the use of parametric tests. Results and conclusions: the main study showed that the results of SPM reliability, validity and item analysis indicated that the SPM test may be considered as an appropriate measure of mental ability for Libyan students. The average IQ for the fourteen tested Libyan age groups (8 years to 21 years) was 81. Gender and region variables were not important factors affecting Libyan students' scores on the SPM test. Gender differences in variability results indicated no consistent tendency. Age, academic discipline and study levels variables were an important factor affecting the Libyan students' scores on the SPM test. In general, all correlation coefficients between SPM and students' academic achievements were statistical significant for all groups. Age and achievement variables were predictors for SPM results, whereas gender and region variables were not significant predictors. The performance of Libyan students on the SPM can be considered lower than students from other countries. Meta-analysis study showed that the average IQ score for developed countries was 95, whereas the average IQ score of developing countries was 82. The IQ score of Libya was similar to that of developing countries. Development status and age variables were concluded as being important factors affecting the SPM. Gender variable was concluded as not being an important factor affecting the SPM. Gender differences in variability on SPM test thus results indicated no consistent tendency. Age and development status variables were predictors for SPM results. Whereas gender variable not significant predictors.The over all results were explained in terms of variation in education, environment,nutrition, child rearing, social income, confidence in test taking, family size, the "individual multiplier" and "social multiplier" and heterosis.
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Babcock, Renee L. "Analysis of adult age differences on the Raven's Advanced Progressive Matrices Test." Diss., Georgia Institute of Technology, 1992. http://hdl.handle.net/1853/29376.

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Isler, William C. (William Charles). "Detection of Malingering on Raven's Standard Progressive Matrices and the Booklet Category Test." Thesis, University of North Texas, 1997. https://digital.library.unt.edu/ark:/67531/metadc279309/.

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The capacity of Raven's Standard Progressive Matrices (SPM) and the Booklet Category Test (BCT) to discriminate between groups of brain-injured, simulated malingering, and normal participants was investigated in this study. Exploratory analyses were also conducted to examine the differences between groups categorized as sophisticated and naive fakers. Clinical decision rules and discriminant function analyses were utilized to identify malingerers. Clinical decision rules ranged in hit rates from 41% to 78%, in sensitivity from 2% to 100%, and in specificity from 86% to 100%. Discriminant functions ranged in hit rates from 81% to 86%, in sensitivity from 68% to 73% and in specificity from 82% to 87%. Overall, the least helpful detection method examined was below chance responding on either measure, while the most efficient was gross errors for SPM.
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Vass, Vasili Arthur. "Standardization of Raven's standard progressive matrices for secondary school African pupils in the Grahamstown region." Thesis, Rhodes University, 1992. http://hdl.handle.net/10962/d1002587.

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Arising out of a need, expressed by Clinical Psychologists in the Grahamstown region, for the fair assessment of secondary School African pupils, norms for the Raven's Standard Progressive Matrices (SPM) were established. Two methods of presentation were used, the first using the original instructions of John Raven translated into the students' first language of Xhosa, hence-forth referred to as the Alternate sample. The second method of presenting the instructions was adapted, to include the use of visual aids and active participation in the instruction phase of the test, hence-forth referred to as the Normative sample. In addition to the establishment of norms, the two methods of test presentation were investigated to see if the method of presentation had an effect on the results of the Raven's SPM. The population was drawn from the three African Secondary Schools in the Grahamstown municipality. The total population consisted of 3 232 students. Classes were randomly sampled across the three schools, with the average age of the Normative sample being 19.3 years. The sample consisted of 812 pupils, 711 in the Normative sample and 101 in the Alternate Sample. The following results and conclusions arose from the study: 1) Norms generated were considerably lower than previously established norms in similar studies. 2) t-Test results indicated that the method of test presentation on the Raven's SPM is important when assessing students that may be regarded as 'disadvantaged'. 3) Respondents scored significantly higher when the method of presenting the instructions ensured a greater understanding of the task demanded of the respondents. 4) The analyses of covariance indicate that male subjects score significantly higher than female subjects, and that there is a significant difference between the ages and educational standard, on the scores of the Raven's SPM. 5) The differences found contradict previous findings using the test, and question the cultural fairness of the test.
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Kunda, Maithilee. "Visual problem solving in autism, psychometrics, and AI: the case of the Raven's Progressive Matrices intelligence test." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/47639.

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Much of cognitive science research and almost all of AI research into problem solving has focused on the use of verbal or propositional representations. However, there is significant evidence that humans solve problems using different representational modalities, including visual or iconic ones. In this dissertation, I investigate visual problem solving from the perspectives of autism, psychometrics, and AI. Studies of individuals on the autism spectrum show that they often use atypical patterns of cognition, and anecdotal reports have frequently mentioned a tendency to "think visually." I examined one precise characterization of visual thinking in terms of iconic representations. I then conducted a comprehensive review of data on several cognitive tasks from the autism literature and found numerous instances indicating that some individuals with autism may have a disposition towards visual thinking. One task, the Raven's Progressive Matrices test, is of particular interest to the field of psychometrics, as it represents one of the single best measures of general intelligence that has yet been developed. Typically developing individuals are thought to solve the Raven's test using largely verbal strategies, especially on the more difficult subsets of test problems. In line with this view, computational models of information processing on the Raven's test have focused exclusively on propositional representations. However, behavioral and fMRI studies of individuals with autism suggest that these individuals may use instead a predominantly visual strategy across most or all test problems. To examine visual problem solving on the Raven's test, I first constructed a computational model, called the Affine and Set Transformation Induction (ASTI) model, which uses a combination of affine transformations and set operations to solve Raven's problems using purely pixel-based representations of problem inputs, without any propositional encoding. I then performed four analyses using this model. First, I tested the model against three versions of the Raven's test, to determine the sufficiency of visual representations for solving this type of problem. The ASTI model successfully solves 50 of the 60 problems on the Standard Progressive Matrices (SPM) test, comparable in performance to the best computational models that use propositional representations. Second, I evaluated model robustness in the face of changes to the representation of pixels and visual similarity. I found that varying these low-level representational commitments causes only small changes in overall performance. Third, I performed successive ablations of the model to create a new classification of problem types, based on which transformations are necessary and sufficient for finding the correct answer. Fourth, I examined if patterns of errors made on the SPM can provide a window into whether a visual or verbal strategy is being used. While many of the observed error patterns were predicted by considering aspects of the model and of human behavior, I found that overall error patterns do not seem to provide a clear indicator of strategy type. The main contributions of this dissertation include: (1) a rigorous definition and examination of a disposition towards visual thinking in autism; (2) a sufficiency proof, through the construction of a novel computational model, that visual representations can successfully solve many Raven's problems; (3) a new, data-based classification of problem types on the SPM; (4) a new classification of conceptual error types on the SPM; and (5) a methodology for analyzing, and an analysis of, error patterns made by humans and computational models on the SPM. More broadly, this dissertation contributes significantly to our understanding of visual problem solving.
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Hayes, Taylor Ray. "A Novel Method for Analyzing Sequential Eye Movements Reveals the Relationship Between Learning and Strategy on Raven's Advanced Progressive Matrices." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1299420177.

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Welch, Jane A. "A comparison of the Matrix Analogies Test-Expanded form and the Raven's Standard Progressive Matrices: European and United States norms." The Ohio State University, 1989. http://rave.ohiolink.edu/etdc/view?acc_num=osu1303142527.

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Bass, Natalie Tanyia. "The Raven's Coloured Progressive Matrices Test : a pilot study for the establishment of normative data for Xhosa-speaking primary school pupils in the Grahamstown region /." Thesis, Rhodes University, 2000. http://eprints.ru.ac.za/1384/.

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Savage-McGlynn, Emily. "Sex differences in general intelligence : a psychometric investigation of group differences in mean and variability as measured by the Raven's Standard Progressive Matrices." Thesis, University of Cambridge, 2011. https://www.repository.cam.ac.uk/handle/1810/241366.

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Researchers and the general public alike continue to debate 'which is the smarter sex'? Research to date suggests that males outperform females, females outperform males, while others find no differences in mean or variance. These inconsistent results are thought to occur for two reasons. First, studies rely on opportunity samples rather than samples that represent the general population. Second, researchers have not availed themselves of advances in psychometrics that allow for identification of bias in test items and the reliable evaluation of group differences. This dissertation addresses these two identified needs in the literature. Using a large representative U.K. sample, 926 seven to 18 year olds were assessed with the Raven's Standard Progressive Matrices Plus (SPM+), a measure considered to be one of the best measures of general intelligence. In assessing a one-factor model of general intelligence, four research aims were addressed. First, confirmatory factor analyses and assessment of measurement invariance revealed that the SPM+ is not biased to either sex. Second, multiple group confirmatory factor analyses revealed there to be no significant differences between males and females in either mean or variance. Third, analyses revealed no significant sex differences in mean or variability in younger or older participants. Finally, method effects of Gestalt and Visuospatial answering strategies explained some of the residual variance in the model. For the overall sample, males were significantly disadvantaged by the visuospatial element of some of the items. For older participants, the influence of the methods effects was equivalent. It can generally be concluded that there are no significant sex differences in mean or variability on the SPM+ suggesting that there is no sex difference in general intelligence. Future research should employ representative samples and robust statistical methodologies to assess sex differences on the Raven's from a multiple factor perspective.
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Books on the topic "Raven’s Progressive Matrices"

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Raven, J. C. Standard progressive matrices. Oxford: Oxford Psychologists Press, 1996.

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Mankwald, Bernhard. Prozessanalysen bei Intelligenztestaufgaben. Pfaffenweiler: Centaurus-Verlagsgesellschaft, 1987.

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Simões, Mário Manuel Rodrigues. Investigações no âmbito da aferição nacional do teste das Matrizes Progressivas Coloridas de Raven (M.P.C.R.). Lisboa: Fundação Calouste Gulbenkian, Fundação para a Ciência e a Tecnologia, Ministério da Ciência e da Tecnologia, 1999.

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Kaplan, Louise. Adolescencia, El Adios Infancia / Ravenbs Progressive Matrices. Ediciones Paidos Iberica, 1991.

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Coloured Progressive Matrices Sets A,ab,b JC Raven. hk lewis & co, 1986.

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Book chapters on the topic "Raven’s Progressive Matrices"

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Leavitt, Victoria M., and Erica Weber. "Raven’s Progressive Matrices." In Encyclopedia of Clinical Neuropsychology, 2937–39. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-57111-9_1069.

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Leavitt, Victoria M., and Erica Weber. "Raven’s Progressive Matrices." In Encyclopedia of Clinical Neuropsychology, 1–3. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56782-2_1069-2.

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Loesche, Patrick. "Raven’s Advanced Progressive Matrices." In Encyclopedia of Personality and Individual Differences, 4307–9. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-319-24612-3_69.

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Loesche, Patrick. "Raven’s Advanced Progressive Matrices." In Encyclopedia of Personality and Individual Differences, 1–4. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-28099-8_69-1.

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Kisielewska, Małgorzata, Mariusz Urbański, and Katarzyna Paluszkiewicz. "Abduction in One Intelligence Test. Types of Reasoning Involved in Solving Raven’s Advanced Progressive Matrices." In Model-Based Reasoning in Science and Technology, 419–35. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-38983-7_23.

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Feis, Yvette Frumkin. "Raven's Progressive Matrices." In Encyclopedia of Cross-Cultural School Psychology, 787. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-0-387-71799-9_344.

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John and Jean Raven. "Raven Progressive Matrices." In Handbook of Nonverbal Assessment, 223–37. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4615-0153-4_11.

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Leavitt, Victoria M. "Raven Progressive Matrices." In Encyclopedia of Clinical Neuropsychology, 2114–15. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-0-387-79948-3_1069.

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"Visual searching impairment in patients with major depressive disorder: performance in the Raven coloured progressive matrices test." In Advances in Neuroregulation and Neuroprotection, 399–410. CRC Press, 2005. http://dx.doi.org/10.1201/b12189-26.

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Conference papers on the topic "Raven’s Progressive Matrices"

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Jahrens, Marius, and Thomas Martinetz. "Solving Raven’s Progressive Matrices with Multi-Layer Relation Networks." In 2020 International Joint Conference on Neural Networks (IJCNN). IEEE, 2020. http://dx.doi.org/10.1109/ijcnn48605.2020.9207319.

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Petretto, Donatella Rita, Paola Grassi, Carmelo Masala, and Eraldo Francesco Nicotra. "Pattern of errors in Raven’s Colored Progressive Matrices and their use in the clinical assessment of intelligence." In 2021 IEEE International Symposium on Medical Measurements and Applications (MeMeA). IEEE, 2021. http://dx.doi.org/10.1109/memea52024.2021.9478720.

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Nicotra, Eraldo Francesco, Paola Grassi, Carmelo Masala, and Donatella Rita Petretto. "A Rasch analysis of Raven’s Colored Progressive Matrices to assess eductive intelligence : A study in a Sardinian sample." In 2018 IEEE International Symposium on Medical Measurements and Applications (MeMeA). IEEE, 2018. http://dx.doi.org/10.1109/memea.2018.8438712.

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Zhukova, E. S., S. L. Artemenkov, and D. B. Bogoyavlenskaya. "To the question of the relationship of giftedness and conscious self-regulation." In INTERNATIONAL SCIENTIFIC AND PRACTICAL ONLINE CONFERENCE. Знание-М, 2020. http://dx.doi.org/10.38006/907345-50-8.2020.104.115.

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The work performed allowed us to determine the correlation of giftedness, level of intelligence, academic success and conscious self-regulation in children of young adolescents. Diagnostics was carried out using the “Creative Field” method (D. B. Bogoyavlenskaya), the “Progressive Matrices” test (J. Raven) and the rapid method «Style of Self-regulation of Children Behavior» SSCB-M1 (V. I. Morosanova). The results were obtained as part of a longitudinal study from primary school to adolescence. Statistical analysis is represented by correlation analysis and the method of constructing regularized networks of patial correlations glasso using the language R. Giftedness is understood by us as the ability to develop activities on our own initiative. Mathematical analysis reveals an indirect connection between giftedness and a cluster of conscious self-regulation through an intelligence index. The negative sign of the connection between intelligence and the “planning” scale is explained by the characteristics of the age under study: the breadth of interests, the situation of choice and the criticality of children with a high level of intelligence, which leads to lower grades.
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Reports on the topic "Raven’s Progressive Matrices"

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Carpenter, Patricia A., Marcel A. Just, and Peter Shell. What One Intelligence Test Measures: A Theoretical Account of the Processing in the Raven Progressive Matrices Test. Fort Belvoir, VA: Defense Technical Information Center, April 1990. http://dx.doi.org/10.21236/ada221448.

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