https://community.jmp.com/t5/Discussions/How-to-compare-several-sets-of-data-modeled-by-a-3-parameter/m-p/666094#M85433 <P>Hi,&nbsp;<BR /><BR />I haven't been able to find a lot of resources for this particular issue.<BR /><BR />Context:<BR />I am working on insect emergence (after metamorphosis). We are recording the proportion of the initial population emerging over time.<BR />For a group of individuals, this phenomenon always follows a 3-parameter logistic model, but different groups will have different parameters.<BR /><BR />We're trying to determine if a treatment will change the parameters of the emergence curve. Any significant changes in one or several of the parameters are relevant<BR /><BR />Ex: if I change the ambiant humidity in my rearing space, will the emergence be quicker (impact on inflexion point, growth rate)? Will it come to a cost to the individuals (impact on asymptote)?<BR /><BR />To answer this question, we are conducting experiments where n-1 groups receive the n-1 levels of a treatment, and one group is a control. We generate n "emergence curves", each one being described by its 3-parameter vector.<BR />Since we know that we may have cohort or environmental effects, the experiment is replicated m times. Within an experiment (nxm curves generated), each curve is modelled from a fixed sample size (usually about 400 individuals). m is relatively small (&lt;10)</P><P>&nbsp;</P><P>How can we conclude that the factor has an effect on one or several parameters of the curves?<BR /><BR />- One option would be to use the "equivalence tests" (parallelism) that are already included in JMP, but they only allow the comparison of two curves at a time. They are described as legacy tests and seem somewhat decried&nbsp;<BR />- Analysing each factor separately (ANOVAs and non-parametric equivalents)? There are some correlations between the parameters of the curves (tested with Pearson's correlation, 2 by 2)<BR />- Using a Manova approach? I'm really not familiar with Manova, so I'd like to know if it would be a valid approach before taking a deep dive in the subject<BR />- Other suggestions?<BR /><BR />I can share some sample data if needed (raw emergence data, or a table with parameters)&nbsp;</P> Mon, 07 Aug 2023 09:14:31 GMT Alexa_Guigue 2023-08-07T09:14:31Z https://community.jmp.com/t5/Discussions/How-to-compare-several-sets-of-data-modeled-by-a-3-parameter/m-p/666094#M85433 <P>Hi,&nbsp;<BR /><BR />I haven't been able to find a lot of resources for this particular issue.<BR /><BR />Context:<BR />I am working on insect emergence (after metamorphosis). We are recording the proportion of the initial population emerging over time.<BR />For a group of individuals, this phenomenon always follows a 3-parameter logistic model, but different groups will have different parameters.<BR /><BR />We're trying to determine if a treatment will change the parameters of the emergence curve. Any significant changes in one or several of the parameters are relevant<BR /><BR />Ex: if I change the ambiant humidity in my rearing space, will the emergence be quicker (impact on inflexion point, growth rate)? Will it come to a cost to the individuals (impact on asymptote)?<BR /><BR />To answer this question, we are conducting experiments where n-1 groups receive the n-1 levels of a treatment, and one group is a control. We generate n "emergence curves", each one being described by its 3-parameter vector.<BR />Since we know that we may have cohort or environmental effects, the experiment is replicated m times. Within an experiment (nxm curves generated), each curve is modelled from a fixed sample size (usually about 400 individuals). m is relatively small (&lt;10)</P><P>&nbsp;</P><P>How can we conclude that the factor has an effect on one or several parameters of the curves?<BR /><BR />- One option would be to use the "equivalence tests" (parallelism) that are already included in JMP, but they only allow the comparison of two curves at a time. They are described as legacy tests and seem somewhat decried&nbsp;<BR />- Analysing each factor separately (ANOVAs and non-parametric equivalents)? There are some correlations between the parameters of the curves (tested with Pearson's correlation, 2 by 2)<BR />- Using a Manova approach? I'm really not familiar with Manova, so I'd like to know if it would be a valid approach before taking a deep dive in the subject<BR />- Other suggestions?<BR /><BR />I can share some sample data if needed (raw emergence data, or a table with parameters)&nbsp;</P> Mon, 07 Aug 2023 09:14:31 GMT https://community.jmp.com/t5/Discussions/How-to-compare-several-sets-of-data-modeled-by-a-3-parameter/m-p/666094#M85433 Alexa_Guigue 2023-08-07T09:14:31Z https://community.jmp.com/t5/Discussions/How-to-compare-several-sets-of-data-modeled-by-a-3-parameter/m-p/666102#M85435 <P>"analysing each factor separately" should be "analysing each parameter separately"</P> Mon, 07 Aug 2023 09:19:56 GMT https://community.jmp.com/t5/Discussions/How-to-compare-several-sets-of-data-modeled-by-a-3-parameter/m-p/666102#M85435 Alexa_Guigue 2023-08-07T09:19:56Z