Method for analyzing non-observed effect concentration (noec) of chemical on organism

A method for analyzing a non-observed effect concentration (NOEC) of a test chemical on a test organism, comprising the following steps:

• 1) conducting a chronic toxicity test on the test organism with the test chemical at different concentrations, and conducting assays to obtain several sets of endpoint effect data;
• 2) classifying each set of the several sets of endpoint effect data obtained in step 1) into one of a plurality of types of data including:
• type a data, type b data, type c data, type d data, and type e data, wherein, the type a data have monotonicity;
• the type b data are binary variables that do not have monotonicity;
• the type c data are continuous variables that do not have monotonicity, and the type c data conform to the normal distribution and homogeneity of variance;
• the type d data are continuous variables that do not have monotonicity, but the type d data only conform to the normal distribution;
• and the type e data are continuous variables that do not have monotonicity, but the type e data do not conform to the normal distribution;
• and
• 3) for each type of data in the plurality of types of data classified in step 2), constructing hypothesis testing models, and according to statistical significance values from hypothesis testing models, among each set of the several sets of endpoint effect data classified into a particular data type, adopting a highest concentration of the test chemical that does not produce a significant effect as NOEC within the particular data type;
• and among the highest concentrations of the test chemical adopted for each type of data in the plurality of data types, adopting a smallest concentration as NOEC of the test chemical on the test organism;
• wherein, a trend test model is adopted when the data are consistent with the type a data;
• a non-parametric paired comparison test model is adopted when the data are consistent with the type b data;
• a paired comparison test model is adopted when the data are consistent with the type c data;
• a heteroscedasticity paired comparison test model is adopted when the data are consistent with the type d data;
• and
• a non-parametric paired comparison test model is adopted when the data are consistent with the type e data.