Jasp software package

Manufactured by JASP Stats

JASP is an open-source statistical software package. Its core function is to provide users with a comprehensive set of statistical analysis tools, including descriptive statistics, t-tests, ANOVA, regression, and more. JASP offers a user-friendly interface and supports a variety of data formats.

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JASP software (143 citations)

5 protocols using jasp software package

Statistical Analysis of Experimental Data

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All experiments were repeated at least three times. Statistical analyses were conducted using the JASP software package (Version 0.14.1, JASP Team, Amsterdam, Netherlands). Student's t-test was used to determine significant differences between two groups, and one-way ANOVA with the least significant difference test was performed to compare more than two groups. All data are presented as mean ± SD, and a value of P < 0.05 was considered statistically significant.

Yang T., Guo L., Fang Y., Liang M., Zheng Y., Pan M., Meng C, & Liu G. (2021). Pericytes of Indirect Contact Coculture Decrease Integrity of Inner Blood-Retina Barrier Model In Vitro by Upgrading MMP-2/9 Activity. Disease Markers, 2021, 7124835.

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Bayesian Statistical Analysis of Neurosurgical Protocols

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All statistical analyses were conducted using ANOVAs within a Bayesian framework using the JASP software package (V.0.14.1; (JASP Team, 2020 )). The ANOVAs used a uniform prior model probability, and the assumption of normality were visualized using a Q-Q plot of the residuals. For both the test–retest reliability and the spatial location analyses patient ID and neurosurgeon ID were included as nuisance variables. For the Dice coefficient and volumetric analysis, the patient ID was included as a nuisance variable. The implementation of the Bayesian ANOVA in JASP relies on the R package BayesFactor (V.0.9.10–2; (Morey and Rouder, 2015 , Rouder et al., 2012 (link))). The resulting Bayes Factors (BF) are interpreted in light of assumptions proposed by (Jeffreys, 1998 ) and adapted by (Wetzels et al., 2011 (link)). Note that the analyses regarding the test–retest reliability, Dice coefficient and volume are based on values calculated in native space whereas the spatial location analysis is based on values in MNI space.

Isaacs B.R., Heijmans M., Kuijf M.L., Kubben P.L., Ackermans L., Temel Y., Keuken M.C, & Forstmann B.U. (2021). Variability in subthalamic nucleus targeting for deep brain stimulation with 3 and 7 Tesla magnetic resonance imaging. NeuroImage : Clinical, 32, 102829.

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Investigating Arithmetic Skill Correlates

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For statistical analyses, the JASP software package (JASP Team, 2017 ) was used to calculate Pearson correlations and their corresponding Bayes Factors between the results of the TTA and the extracted mean values of the ROIs. The Bayesian approach has the advantage to quantify the evidence that data provide for one hypothesis over another (Andraszewicz et al., 2015 ). Accordingly, Bayes factors (BF₁₀) of 1, 1–3, 3–10, 10–30, 30–100, or > 100 respectively point towards no, anecdotal, substantial, strong, very strong, or decisive evidence for the hypothesis of an association between two variables (Jeffreys, 1961 ). The results of the frequentist approach to statistical testing are also reported. For these analyses, the Bonferroni method of controlling for multiple comparisons (p = Target Alpha Level/number of ROIs; p = .05/42 = 0.001 for voxel-based morphometry and p = .05/78 = 0.0006 for cortical complexity) was implemented. Partial correlations were also calculated with IQ and motor reaction time simultaneously added as control variables. To test the specificity of the results, the significant correlations were also calculated with our reading measure as to check whether any observed associations with arithmetic are also observed with another symbolic academic skill (i.e., reading), measured in a similar, timed, way.

Polspoel B., Vandermosten M, & De Smedt B. (2019). The association of grey matter volume and cortical complexity with individual differences in children’s arithmetic fluency. Neuropsychologia, 137, 107293.

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Assessing Knowledge and Emotions in Science Education

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The data were analysed using the JASP software package (Amsterdam, 0.16.4.0). After application of the Shapiro-Wilk test, the conclusion was that the sample did not follow a normal distribution, so non-parametric statistics were used for data analysis.
Both questionnaires, pre and post-test, have been validated by five experts in Experimental Sciences Education, who read, corrected, and suggested improvements which were then incorporated. The questionnaire was in Spanish. The knowledge questionnaire used (pre-test and post-test) is a validated questionnaire published by Giraldo-Toro et al. (2015). The emotional questionnaire used is a validated questionnaire published by authors (Hernández-Barco et al., 2021b ). The value of McDonald's ω allowed us to know the questionnaire's reliability. The result was a value of ω = 0.814, which corresponds to acceptable reliability since it is between 0.70 and 0.90 (Ventura-León and Caycho-Rodríguez, 2017 ).

Míriam Andrea H.B., Jesús S.M., Isaac C.C, & Florentina C.C. (2022). Is sustainability an exhausted concept? Bridging the gap from environmental awareness to emotional proficiency in science education through integral sustainability. Heliyon, 8(12), e12546.

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Bayesian Analysis of Drug Effects

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Drug effects on model-free performance measures and fMRI parameter estimates extracted at specific peaks were analyzed via Bayesian repeated measures ANOVAs using the JASP software package (Version 0.16.3)^{64 (link)}. The normality of residuals was verified via Q-Q-plots, which showed no credible evidence for deviations from normality (see Supplemental Fig. S18).

Chakroun K., Wiehler A., Wagner B., Mathar D., Ganzer F., van Eimeren T., Sommer T, & Peters J. (2023). Dopamine regulates decision thresholds in human reinforcement learning in males. Nature Communications, 14, 5369.

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