TY - GEN
T1 - Using Multiple Regression Model to Evaluate the Performance of Laboratory Information Management System
T2 - 4th International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2024
AU - Yuen, Norton H.Y.
AU - Tang, Fanny W.F.
AU - Li, Jimmy C.H.
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - In this paper, the researchers will analyze the performance of the Laboratory Information Management System (LIMS) with the help of a structured questionnaire and utilize multiple regression with backward elimination to construct a regression model. Based on the scale of 12-20, the survey assesses several aspects of LIMS performance: usability feature stability after being updated support functions provided in LIMS Operations. The example data suggests that the multiple regression model which is in widespread use for LIMS performance evaluations is appropriate. The results support the model's ability to distinguish the chief causes of a system's behavior, and also provide a strong background for methodologies used for future work. However, though this study was only a simulation which has limited sample size, it opened up the unknown field of applying multiple regression analyses to LIMS.
AB - In this paper, the researchers will analyze the performance of the Laboratory Information Management System (LIMS) with the help of a structured questionnaire and utilize multiple regression with backward elimination to construct a regression model. Based on the scale of 12-20, the survey assesses several aspects of LIMS performance: usability feature stability after being updated support functions provided in LIMS Operations. The example data suggests that the multiple regression model which is in widespread use for LIMS performance evaluations is appropriate. The results support the model's ability to distinguish the chief causes of a system's behavior, and also provide a strong background for methodologies used for future work. However, though this study was only a simulation which has limited sample size, it opened up the unknown field of applying multiple regression analyses to LIMS.
KW - Data Analysis
KW - Laboratory Efficiency
KW - Laboratory Information Management System (LIMS)
KW - Multiple Regression Model
KW - Performance Evaluation
KW - Product Testing
KW - Questionnaire Survey
KW - Testing Inspection and Certification (TIC) Industry
UR - https://www.scopus.com/pages/publications/85216018536
U2 - 10.1109/ICECCME62383.2024.10796876
DO - 10.1109/ICECCME62383.2024.10796876
M3 - Conference contribution
AN - SCOPUS:85216018536
T3 - International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2024
BT - International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2024
Y2 - 4 November 2024 through 6 November 2024
ER -