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Jmp statistical software package

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JMP is a statistical software package developed by SAS Institute. It provides tools for data analysis, visualization, and modeling. JMP offers a range of functionalities for handling and exploring data, as well as performing advanced statistical analyses. The software is designed to assist users in making data-driven decisions.

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R software version 4, by R Project for Statistical Computing (1 mentions) Sas 9, by SAS Institute (1 mentions)

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JMP software (1534 citations) JMP statistical software (341 citations) JMP software package (75 citations) JMP statistical package (71 citations) JMP Statistical Software Package 9 (3 citations) JMP 11 statistical software package (2 citations) JMP Statistical Software Package 14 (2 citations) JMP 9.0 statistical software package (2 citations)

43 protocols using jmp statistical software package

1

Survival Analysis of Surgical Spacer Placement

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The MST and OS rates were calculated from the date of diagnosis and surgical spacer placement to the date of the event or last follow-up using Kaplan–Meier methods. Freedom from progression and local control rates were calculated from the date of surgical spacer placement to the date of the event or last follow-up using Kaplan–Meier methods. Differences in the survival rates between the groups were compared using the log-rank test. The unpaired Student’s t-test was used to compare the parameters of the dose-volume histograms. A value of p < 0.05 was considered statistically significant in all the analyses. All statistical analyses were performed using the JMP statistical software package, version 13 (SAS Institute, Japan).
Lee D., Komatsu S., Terashima K., Toyama H., Matsuo Y., Takahashi D., Suga M., Nishimura N., Tai K., Kido M., Demizu Y., Tokumaru S., Okimoto T., Sasaki R, & Fukumoto T. (2021). Surgical spacer placement for proton radiotherapy in locally advanced pancreatic body and tail cancers: initial clinical results. Radiation Oncology (London, England), 16, 3.
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2

Survival Analysis of Risk Factors

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Continuous variables are presented as the means ± standard deviation. The chi‐square test, Fisher's exact test and the Mann–Whitney U‐test were used as appropriate to evaluate the association between two variables. The Steel‐Dwass multiple comparison test was applied to compare the data of the four groups. The survival correlations are illustrated with Kaplan–Meier curves, and survival analyses were performed using the log‐rank test. We conducted a Cox proportional hazards regression analysis to estimate the hazard ratios for positive risk factors for death. A two‐sided p‐value of <0.05 was considered significant. The data analysis was conducted with the JMP statistical software package (version 9.0.2; SAS Institute, Cary, NC).
Iura K., Kohashi K., Hotokebuchi Y., Ishii T., Maekawa A., Yamada Y., Yamamoto H., Iwamoto Y, & Oda Y. (2015). Cancer‐testis antigens PRAME and NY‐ESO‐1 correlate with tumour grade and poor prognosis in myxoid liposarcoma. The Journal of Pathology: Clinical Research, 1(3), 144-159.
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3

Statistical Analysis of Associations

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We used the Fisher's exact test and Mann-Whitney U test as appropriate to evaluate associations between two variables. Two-sided P-values less than 0.05 were considered to indicate statistical significance. The data analyses were conducted with the JMP statistical software package (version 12.0.2; SAS Institute, Cary, NC).
Abe T., Kohashi K., Takemoto J., Kinoshita F., Eto M, & Oda Y. (2018). Clinicopathological Significance and Antitumor Effect of MPHOSPH1 in Testicular Germ Cell Tumor. Journal of Cancer, 9(23), 4440-4448.
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4

Survival Analysis of Brain Metastases in Sarcoma

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The BM‐free survival (BMFS) was defined as the interval from the date of the diagnosis of primary sarcoma to the date of BM, and the post‐BM survival (PBMS) was determined from the date of BM to the date of tumor death or last follow‐up. The duration between initial metastasis and BM was defined from the date of extracranial metastasis to the date of BM. The mean duration was defined as the cut‐off point for the duration between initial metastasis and BM. Survival curves were calculated using the Kaplan–Meier curve for each factor. Differences in survival were assessed by the log‐rank test, and statistical significance was defined as p < 0.05.
Data analyses were performed using the JMP statistical software package (version 14.0.0; SAS Institute Inc.).
Toda Y., Kobayashi E., Kubota D., Miyakita Y., Narita Y, & Kawai A. (2023). A retrospective analysis of the prognosis of Japanese patients with sarcoma brain metastasis. Cancer Medicine, 12(8), 9471-9481.
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5

Validating Asthma Diagnosis Using NLP-API

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Performance of NLP-API was assessed for both criterion and construct validity. For criterion validity, we calculated agreement rate, Kappa index, and validation index (sensitivity, specificity, positive predictive value, and negative predictive value) for concordance in asthma status between NLP-API and manual chart review as gold standard. Using logistic regression models, construct validity was assessed by determining the association of asthma status ascertained by NLP-API with the known risk factors for asthma as NLP-API is expected to be correlated with the known risk factors if NLP algorithm reflects true asthma. The associations were summarized by odds ratios and their corresponding 95% confidence intervals. All analyses were performed using JMP statistical software package (Ver 10; SAS Institute, Inc., Cary, NC).
Kaur H., Sohn S., Wi C.I., Ryu E., Park M.A., Bachman K., Kita H., Croghan I., Castro-Rodriguez J.A., Voge G.A., Liu H, & Juhn Y.J. (2018). Automated chart review utilizing natural language processing algorithm for asthma predictive index. BMC Pulmonary Medicine, 18, 34.
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6

Statistical Analysis of Experimental Data

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Data are expressed as the mean ± standard deviation for normally distributed data, and medians (interquartile range) for data with skewed distributions. The Mann‐Whitney U‐test and Wilcoxon signed‐rank test were used for data analysis. A P‐value <0.05 denoted the presence of a statistically significant difference. All statistical analyses were carried out using the JMP statistical software package, version 10.0.2 (SAS Institute, Cary, NC, USA).
Tsunemi A., Sato J., Kurita M., Wakabayashi Y., Waseda N., Koshibu M., Shinohara M., Ozaki A., Nakamura H., Hirano N., Ikeda F., Satoh H, & Watada H. (2020). Effect of real‐life insulin pump with predictive low‐glucose management use for 3 months: Analysis of the patients treated in a Japanese center. Journal of Diabetes Investigation, 11(6), 1564-1569.
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7

DUSP4 expression impacts proliferation

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Statistical analyses in this study were carried out with the JMP statistical software package (SAS Institute, Cary, NC, USA). The effects of re‐expression of DUSP4 on cell proliferation and invasiveness was examined using anova and Student's t‐test. Comparisons of DUSP4 scores in normal epithelium, superficial region, and deep region were evaluated using Fisher's exact probability test. Differences at P ≤ .05 were considered statistically significant.
Ichimanda M., Hijiya N., Tsukamoto Y., Uchida T., Nakada C., Akagi T., Etoh T., Iha H., Inomata M., Takekawa M, & Moriyama M. (2017). Downregulation of dual‐specificity phosphatase 4 enhances cell proliferation and invasiveness in colorectal carcinomas. Cancer Science, 109(1), 250-258.
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8

Asthma and Appendicitis Risk Factors

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We summarized characteristics of appendicitis cases and matched controls using descriptive statistics. Association of each characteristic, including history of asthma and asthma status based on current symptoms (i.e., no asthma, inactive asthma, and active asthma), with risk of appendicitis was tested using conditional logistic regression models. Additional multivariable conditional analysis was performed to further assess the association of asthma, controlling for pertinent covariates and confounders having association p-values less than 0.2 from univariate analysis (Greenland criteria).42 Odds ratio (OR) and its 95% confidence interval (CI) were presented for all analysis. All analyses were performed using JMP statistical software package (Ver 10.0.0; SAS Institute, Inc, Cary, NC).
Hasassri M.E., Jackson E.R., Ghawi H., Ryoo E., Wi C.I., Bartlett M.G., Volcheck G.W., Moir C.R., Ryu E, & Juhn Y.J. (2016). Asthma and risk of appendicitis in children: a population-based case-control study. Academic pediatrics, 17(2), 205-211.
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9

Statistical Analysis of Flow Cytometry

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Analyses of FACS data such as calculation of absolute cell numbers and comparisons of means/medians of each surface phenotype under different experimental conditions were carried out using FlowJo software (TreeStar). Statistical analyses were performed with the JMP statistical software package (SAS Institute) or with Origin software. Histopathological data were analyzed by ANOVA. Flow cytometry data and ELISA data were evaluated by t-test. The differences between study and control groups were tested by Fisher's Exact test. A P<0.05 was considered statistically significant.
Kundu-Raychaudhuri S., Chen Y.J., Wulff H, & Raychaudhuri S.P. (2014). Kv1.3 in Psoriatic Disease: PAP-1, a small molecule inhibitor of Kv1.3 is effective in the SCID mouse psoriasis - xenograft model. Journal of autoimmunity, 55, 63-72.
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10

Evaluating Asthma Ascertainment Methods

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We summarized the prevalence of asthma by API and PAC alone. To assess criterion validity of API, we calculated overall agreement and Cohen’s unweighted kappa index between retrospective API and PAC. To further determine the correlation between API and PAC, we calculated the specific proportionate agreement for positive (2a / (2a+b+c); a (positive for both criteria), b (positive for API only), c (positive for PAC only), d (negative for both criteria)) and the specific proportionate agreement for negative (2d / (2d+b+c)).(29 (link)) To determine the construct validity of each asthma ascertainment method, we assessed the associations of known risk factors for asthma with each asthma criteria by using logistic regression models. The associations were summarized by calculating odds ratios (ORs) and their corresponding 95% confidence intervals (CIs). All analyses were performed using JMP statistical software package (Ver 9.0.1; SAS Institute, Inc, Cary, NC).
Wi C.I., Park M.A, & Juhn Y.J. (2014). Development and Initial Testing of Asthma Predictive Index for a Retrospective Study: An Exploratory Study. The Journal of asthma : official journal of the Association for the Care of Asthma, 52(2), 183-190.
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