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Journal articles on the topic 'Chi-square test'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Kilic, Selim. "Chi-square Test." Journal of Mood Disorders 6, no. 3 (2016): 180. http://dx.doi.org/10.5455/jmood.20160803110534.

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2

Daya, Salim. "Chi-square test." Evidence-based Obstetrics & Gynecology 3, no. 1 (2001): 3–4. http://dx.doi.org/10.1054/ebog.2001.0223.

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3

Franke, Todd Michael, Timothy Ho, and Christina A. Christie. "The Chi-Square Test." American Journal of Evaluation 33, no. 3 (2011): 448–58. http://dx.doi.org/10.1177/1098214011426594.

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4

Pandis, Nikolaos. "The chi-square test." American Journal of Orthodontics and Dentofacial Orthopedics 150, no. 5 (2016): 898–99. http://dx.doi.org/10.1016/j.ajodo.2016.08.009.

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5

Germogenov, A. P., and A. F. Ronzhin. "A Sequential Chi-Square Test." Theory of Probability & Its Applications 29, no. 2 (1985): 397–403. http://dx.doi.org/10.1137/1129052.

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6

Wu, Jyh-Shyang, and Wen-Shuenn Deng. "Averaged shifted chi-square test." Journal of Nonparametric Statistics 24, no. 1 (2012): 39–57. http://dx.doi.org/10.1080/10485252.2011.608849.

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7

Koletsi, Despina, and Nikolaos Pandis. "The chi-square test for trend." American Journal of Orthodontics and Dentofacial Orthopedics 150, no. 6 (2016): 1066–67. http://dx.doi.org/10.1016/j.ajodo.2016.10.001.

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8

Leorato, S. "A chi-square-type test for covariances." Journal of Nonparametric Statistics 18, no. 2 (2006): 159–80. http://dx.doi.org/10.1080/10485250600687051.

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9

บวรกิติวงศ์, สุชาดา. "ความแกร่งของสถิติทดสอบไคสแควร์ Robustness of the Chi-square Test". Journal of Education Studies 44, № 3 (2016): 212–20. http://dx.doi.org/10.58837/chula.educu.44.3.14.

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10

Rofiqoh, Siti Nur Indah, Ririn Triratnasari, Nelly Rahmatillah, Fatin Fadhilah Hasib, and Alimin Alimin. "Uji chi-square pada Penelitian Ekonomi Syariah." International Conference on Islamic Economic (ICIE) 2, no. 1 (2023): 152–61. http://dx.doi.org/10.58223/icie.v2i1.200.

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In Islamic economic research, we may collect categorical variable data. Using statistical analysis, chi-square test can be an alternative to evaluate those data. Furthermore, the analysis of chi-square test can be aimed at evaluating the differences between study groups according to the assign degree of error. This article also explains the purpose of chi-square test, the Karl Person chi-square hypothesis, what type of data can use in chi-square test, the assumptions of chi-square analysis and also the rule to analyze categorical variables data in sharia economics research.

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11

Kneidel, Ken. "How the Chi-Square Test Works: A Lesson." American Biology Teacher 58, no. 7 (1996): 420–23. http://dx.doi.org/10.2307/4450195.

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12

Alalouf, I. S. "The Chi Square Test With Both Margins Fixed." Communications in Statistics - Theory and Methods 16, no. 1 (1987): 29–43. http://dx.doi.org/10.1080/03610928708829350.

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13

Norman, Geofrey R., and David L. Streiner. "Body counts and biostatistics: the chi-square test." Community Oncology 7, no. 6 (2010): 286–87. http://dx.doi.org/10.1016/s1548-5315(11)70571-x.

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14

Da, Ren, and Ching-Fang Lin. "Sensitivity Analysis of the State Chi-Square Test." IFAC Proceedings Volumes 29, no. 1 (1996): 6596–601. http://dx.doi.org/10.1016/s1474-6670(17)58741-8.

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15

Curtis, Keith, and Scott T. Youngquist. "Part 21: Categoric Analysis: Pearson Chi-Square Test." Air Medical Journal 32, no. 4 (2013): 179–80. http://dx.doi.org/10.1016/j.amj.2013.04.007.

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16

Pavlov, A. V. "Large deviation theorems for the chi-square test." Russian Mathematical Surveys 51, no. 1 (1996): 158–59. http://dx.doi.org/10.1070/rm1996v051n01abeh002760.

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17

Onoghojobi, B., and N. P. Olewuezi. "CHI-SQUARE STATISTIC AS A SCORE TEST STATISTIC." Far East Journal of Theoretical Statistics 51, no. 1-2 (2015): 1–15. http://dx.doi.org/10.17654/ts051120001.

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18

Viollaz, A. J. "On the reliability of the chi-square test." Metrika 33, no. 1 (1986): 135–42. http://dx.doi.org/10.1007/bf01894740.

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19

Kahn, James A., and Masao Ogaki. "A chi-square test for a unit root." Economics Letters 34, no. 1 (1990): 37–42. http://dx.doi.org/10.1016/0165-1765(90)90178-4.

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20

Nurhasanah, Nurhasanah, Rito Goejantoro, and Suyitno Suyitno. "Penerapan Metode Klasifikasi Chi-Square Automatic Interaction Detection dan Exhaustive Chi-Square Automatic Interaction Detection." EKSPONENSIAL 13, no. 1 (2022): 29. http://dx.doi.org/10.30872/eksponensial.v13i1.877.

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The Chi-Square Automatic Interaction Detection (CHAID) and Exhaustive CHAID methods are nonparametric statistical methods that can be used to classify. CHAID and Exhaustive CHAID were used to determine the significant relationship between the dependent variable and the independent variables based on the chi-square independence test. This study was applied to data on the study period of students of FMIPA UNMUL batch 2014. Based on the CHAID and Exhaustive CHIAD methods, it can be seen that the dependent variable of the study period has a significant relationship with the independent variable, n

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21

Singhal, Richa, and Rakesh Rana. "Chi-square test and its application in hypothesis testing." Journal of the Practice of Cardiovascular Sciences 1, no. 1 (2015): 69. http://dx.doi.org/10.4103/2395-5414.157577.

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22

Adekpedjou, Akim, WITHANAGE A. De Mel, and Gideon KD Zamba. "Data Dependent Cells Chi-Square Test With Recurrent Events." Scandinavian Journal of Statistics 42, no. 4 (2015): 1045–64. http://dx.doi.org/10.1111/sjos.12150.

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23

Da, Ren, and Ching-Fang Lin. "Sensitivity analysis algorithm for the state chi-square test." Journal of Guidance, Control, and Dynamics 19, no. 1 (1996): 219–22. http://dx.doi.org/10.2514/3.21601.

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24

Daya, Salim. "Chi-square test for larger (r×c) contingency tables." Evidence-based Obstetrics & Gynecology 3, no. 2 (2001): 59–60. http://dx.doi.org/10.1054/ebog.2001.0248.

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25

Daya, Salim. "Chi-square test for trend (2×c contingency table)." Evidence-based Obstetrics & Gynecology 3, no. 3 (2001): 116–17. http://dx.doi.org/10.1054/ebog.2001.0275.

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26

GLINER, JEFFREY A., GEORGE A. MORGAN, and ROBERT J. HARMON. "The Chi-Square Test and Accompanying Effect Size Indices." Journal of the American Academy of Child & Adolescent Psychiatry 41, no. 12 (2002): 1510–12. http://dx.doi.org/10.1097/00004583-200212000-00024.

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27

Ottenbacher, Kenneth J. "The chi-square test: Its use in rehabilitation research." Archives of Physical Medicine and Rehabilitation 76, no. 7 (1995): 678–81. http://dx.doi.org/10.1016/s0003-9993(95)80639-3.

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28

Fong, Joseph, Shi Ming Huang, and Hsiang Yuan Hsueh. "Online analytical mining association rules using Chi-square test." International Journal of Business Intelligence and Data Mining 2, no. 3 (2007): 311. http://dx.doi.org/10.1504/ijbidm.2007.015487.

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29

Dijkers, Marcel P. "Misuse of the Pearson chi-square test of association." Archives of Physical Medicine and Rehabilitation 86, no. 3 (2005): 602. http://dx.doi.org/10.1016/j.apmr.2004.12.019.

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30

Ahad, Nor Aishah, Friday Zinzendoff Okwonu, Joshua Sarduana Apanapudor, Festus Irimisose Arunaye, and Sunday Amoju Ojobor. "Chi-square and Adjusted Standardised Residual Analysis." ASM Science Journal 18 (November 6, 2023): 1–11. http://dx.doi.org/10.32802/asmscj.2023.985.

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In hypothesis testing, inference is made by comparing the computed test statistic and the critical value which rely on a specified level of significance and degrees of freedom. This paper examines various study variables to assess whether there exists an interdependency between relationship intimacy and these variables. The chi-square test, likelihood ratio test, the adjusted standardised residual, and the proposed benchmark methods are applied to determine the acceptance or rejection of the null hypothesis and the individual category contribution that enhanced the inference. The comparative a

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31

Lugo-Armenta, Jesus Guadalupe, Luis Roberto Pino-Fan, and Blanca Rosa Ruiz Hernandez. "Chi-square Reference Meanings: a Historical-epistemological Overview." Revemop 3 (June 21, 2021): e202108. http://dx.doi.org/10.33532/revemop.e202108.

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The present article shows a historical-epistemological study on the Chi-square statistic. In which theoretical-methodological notions from the Onto-Semiotic Approach (OSA) of mathematical cognition and instruction were used to identify four problems that have been key to the evolution of the Chi-square statistic: the Goodness-of-fit-test, the test of independence, the test of homogeneity and distribution. Furthermore, various meanings of the Chi-square statistic were recognized in the mathematical-statistical practices that are used to solve each of those problems. These meanings could help to

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32

Wang, Hung-Hsiang, and Chih-Ping Chen. "Comparison of Chi-Square Test and Representative Decision Tree in Features that Influence Vehicle Style." International Journal of Machine Learning and Computing 11, no. 5 (2021): 333–38. http://dx.doi.org/10.18178/ijmlc.2021.11.5.1057.

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33

White, Wes. "Connecting Independence and the Chi-Square Statistic." Mathematics Teacher 94, no. 2 (2001): 134–36. http://dx.doi.org/10.5951/mt.94.2.0134.

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The chi-square statistic is used to test goodness of fit, homogeneity of proportions, and independence. Although the first two uses were at least somewhat new to my students, the concept of independence was not. This article begins by reviewing the use of the chi-square statistic for goodness of fit and then looks at how I have helped my students relate their earlier work with independence to the use of the chi-square statistic.

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34

Kang, Hongzhaoning, Gang Liu, Zhengping Wu, Yumin Tian, and Lizhi Zhang. "A Modified FlowDroid Based on Chi-Square Test of Permissions." Entropy 23, no. 2 (2021): 174. http://dx.doi.org/10.3390/e23020174.

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Android devices are currently widely used in many fields, such as automatic control, embedded systems, the Internet of Things and so on. At the same time, Android applications (apps) always use multiple permissions, and permissions can be abused by malicious apps that disclose users’ privacy or breach the secure storage of information. FlowDroid has been extensively studied as a novel and highly precise static taint analysis for Android applications. Aiming at the problem of complex detection and false alarms in FlowDroid, an improved static detection method based on feature permission and ris

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35

Hinoue, Tomohiko, Atsuko Miyaji, and Takatomi Wada. "The Security of RC6 against Asymmetric Chi-square Test Attack." IPSJ Digital Courier 3 (2007): 600–609. http://dx.doi.org/10.2197/ipsjdc.3.600.

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36

Inglot, Tadeusz, and Alicja Janic-Wróblewska. "Data driven chi-square test for uniformity with unequal cells." Journal of Statistical Computation and Simulation 73, no. 8 (2003): 545–61. http://dx.doi.org/10.1080/0094965021000060918.

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37

Brumback, B., and M. Srinath. "A Chi-square test for fault-detection in Kalman filters." IEEE Transactions on Automatic Control 32, no. 6 (1987): 552–54. http://dx.doi.org/10.1109/tac.1987.1104658.

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38

Vihari, K. Naga, A. Vani, and M. Bhupathi Naidu. "Implementing chi-square test for goodness of fit in java." International Journal of Applied Research 10, no. 8 (2024): 01–03. http://dx.doi.org/10.22271/allresearch.2024.v10.i8a.11908.

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39

Daya, Salim. "Paired comparisons in contingency tables – the McNemar chi-square test." Evidence-based Obstetrics & Gynecology 4, no. 2 (2002): 56–57. http://dx.doi.org/10.1054/ebog.2002.0050.

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40

Bai, Z. D., and Xuming He. "A chi-square test for dimensionality with non-Gaussian data." Journal of Multivariate Analysis 88, no. 1 (2004): 109–17. http://dx.doi.org/10.1016/s0047-259x(03)00056-3.

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41

Jung, Sin-Ho, Seung-Ho Kang, and Chul Ahn. "Chi-Square Test for R×CContingency Tables with Clustered Data." Journal of Biopharmaceutical Statistics 13, no. 2 (2003): 241–51. http://dx.doi.org/10.1081/bip-120019269.

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42

Gilbert, Gregory E., and Susan Prion. "Making Sense of Methods and Measurement: The Chi-Square Test." Clinical Simulation in Nursing 12, no. 5 (2016): 145–46. http://dx.doi.org/10.1016/j.ecns.2015.12.013.

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43

Kumar, Ashok. "The Chi-Square test: a frequency data based statistical device." Journal of Universal College of Medical Sciences 3, no. 3 (2015): 53–55. http://dx.doi.org/10.3126/jucms.v3i3.24250.

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“Cause Effect” relationships are very important and play a most vital and significant role in medical researchers to reveal efficacy of medication as preventive and curative measures towards control and eradication of various diseases and morbidity factors. The present paper, in this direction is an attempt to highlight the main applicability of - test ( chi- square test ) ; a most appropriate statistical device in testing statistical significance of the above mentioned relationships in studying impact of one on the other ; supplemented by a few citations thereof.

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44

Satorra, Albert, and Peter M. Bentler. "Ensuring Positiveness of the Scaled Difference Chi-square Test Statistic." Psychometrika 75, no. 2 (2009): 243–48. http://dx.doi.org/10.1007/s11336-009-9135-y.

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45

Berry, Kenneth J., and Paul W. Mielke. "An Asymmetric Test of Homogeneity of Proportions." Psychological Reports 87, no. 1 (2000): 259–65. http://dx.doi.org/10.2466/pr0.2000.87.1.259.

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An asymmetrical test of homogeneity of proportions possesses distinct advantages over a symmetrical test. The symmetric chi square test of homogeneity is widely employed in psychological research. An asymmetrical alternative to the chi square test of homogeneity is proposed and described.

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46

Li, Jie, Jiajuan Liang, Jiangrui Kang, and Xiaoling Peng. "Representative Points Based Goodness-of-fit Test for Location-scale Distributions." Journal of Physics: Conference Series 2890, no. 1 (2024): 012003. http://dx.doi.org/10.1088/1742-6596/2890/1/012003.

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Abstract The classical Pearson-Fisher chi-square test is a general approach to testing goodness-of-fit for univariate data. There is a considerable amount of discussion on how to effectively apply this test to practical goodness-of-fit problems in the literature. However, the choice of optimal grouping intervals in constructing the chi-square statistic still remains arguable and uncertain. Based on the statistical principle of defining the mean-square-error representative points, we propose to employ the statistical representative points to construct the Pearson-Fisher chi-square test. We carr

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47

Syoffnelli, Syoffnelli, Zulfan Saam, and Thamrin Thamrin. "Pengaruh Program Adiwiyata Terhadap Pengetahuan Perilaku dan Keterampilan Siswa dan Guru dalam Mengelola Lingkungan pada SMK di Kabupaten Pelalawan." Dinamika Lingkungan Indonesia 3, no. 1 (2016): 16. http://dx.doi.org/10.31258/dli.3.1.p.16-23.

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Abstrak: The study aimed to determine adiwiyata program effects on knowledge, behaviour and skills of students and teachers also compared schools that have implemented the adiwiyata program with schools that have not implemented adiwiyata program. This study is a quantitative descriptive research. The subjects were students and teachers of SMK Negeri 1 Pangkalan Kerinci and SMK Negeri 1 Bunut with total 194 people. The data collection methode used were questionnaires, interviews and observations, data analysis technique using Chi-square test with SPSS version 20 for windows. Results of the stu

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48

OLANUSI, Dr J. A., and S. A. SAMUEL. "Application of Chi-Square Test to Determine Architectural Impact on Church Patronage." International Journal of Research and Innovation in Social Science VII, no. VI (2023): 605–16. http://dx.doi.org/10.47772/ijriss.2023.7646.

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This paper provides a crucial analysis of chi square test. The concept of chi square test as well as the various and varying scales of disparity in chi square test availability are discussed. The Chi-square is the most commonly used significance test for categorical variables in the social sciences as well as architecture The tool has been employed as a means of assessing the relationship between two categorical variables as tabulated against each other in a contingency table. The test compares the actual values in the cells of the table with those that would be expected under conditions of in

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49

Rahmadhani, Mayasari, Mayang Sari Ayu, and Rosa Zorayatamin Damanik. "Affecting factors on the incidence of Stunting in children aged 0 – 59 months in the working area of Amplas community health center in Medan city." International Journal of Public Health Excellence (IJPHE) 3, no. 2 (2024): 721–28. http://dx.doi.org/10.55299/ijphe.v3i2.773.

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Stunting is one of the targets of the Sustainable Developments Goals in order to achieve the goals by 2030, with two indicators, including eliminating famine and malnutrition. Hence, by 2025 it has been predicted that the stunting rate will be 40% reduced. The purpose of this study was to determine the factors that affect the incidence of stunting in 0-59 months children. This is an analytic observational study with a case control approach. In this study, 20 samples were selected using the total sampling technique that are divided into two groups. This study were conducted from October to Nove

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50

Kossovsky, Alex Ely. "On the Mistaken Use of the Chi-Square Test in Benford’s Law." Stats 4, no. 2 (2021): 419–53. http://dx.doi.org/10.3390/stats4020027.

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Benford’s Law predicts that the first significant digit on the leftmost side of numbers in real-life data is distributed between all possible 1 to 9 digits approximately as in LOG(1 + 1/digit), so that low digits occur much more frequently than high digits in the first place. Typically researchers, data analysts, and statisticians, rush to apply the chi-square test in order to verify compliance or deviation from this statistical law. In almost all cases of real-life data this approach is mistaken and without mathematical-statistics basis, yet it had become a dogma or rather an impulsive ritual

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