QA

Pharmpy currently creates results after a PsN qa run.

The qa results

Overview

The overview dofv table lists the most impactful modifications identified by QA. More details for each result can be found in the individual sections.

The table shows an overview of possible modifications to different model aspects, expected improements in OFV as well as number of additional parameters used.

			dofv	df
section	run	dvid
parameter_variability	fullblock	NaN	2.592698	1.0
	boxcox	NaN	2.197887	2.0
	tdist	NaN	0.007493	2.0
	add_etas	NaN	NaN	NaN
	iov	NaN	NaN	NaN
covariates	frem	NaN	4.521171	4.0
	ET1APGR-2	NaN	2.487930	1.0
residual_error_model	dtbs	1.0	13.910000	2.0
	time_varying	1.0	8.030000	2.0

Structural bias

This section aims at diagnosing the structural component of the model. It does so by estimating the mean difference between model predictions and observations as a function of several independent variables.

The structural_bias table shows the CWRES and CPRED given different bins of the independent variable.

			binmin	binmax	cwres	cpred
idv	dvid	binid
TIME	1	1	0.00	2.00	0.28	-6
		2	2.00	2.55	0.12	-2
		3	2.55	11.00	-0.29	6
		4	11.00	47.25	0.04	-1
		5	47.25	63.50	-0.39	7
		6	63.50	83.10	0.20	-4
		7	83.10	112.30	0.11	-2
		8	112.30	135.50	-0.29	5
		9	135.50	159.80	0.19	-4
		10	159.80	390.00	-0.02	1
TAD	1	1	0.00	1.50	0.06	-1
		2	1.50	2.00	0.41	-8
		3	2.00	3.00	-0.13	3
		4	3.00	6.00	-0.06	1
		5	6.00	11.00	-0.18	3
		6	11.00	11.50	0.54	-10
		7	11.50	11.70	-0.24	4
		8	11.70	14.00	0.06	-1
		9	14.00	258.00	0.07	-1
PRED	1	1	8.00	17.67	0.19	-5
		2	17.67	19.50	0.10	-1
		3	19.50	20.13	-0.17	3
		4	20.13	21.39	-0.01	0
		5	21.39	24.32	0.24	-4
		6	24.32	26.63	0.06	-1
		7	26.63	28.70	0.05	-1
		8	28.70	31.28	-0.05	1
		9	31.28	36.34	0.07	0
		10	36.34	54.00	-0.47	9

Fullblock

This section shows the effect of including a full block correlation struture in the base mdel.

The fullblock_parameters contains the estimated standard deviation (sd), correlation (corr) and expected improvement in OFV after inclusion of a full block correlation structure of the random effects.

	new	old
OMEGA(1,1)	0.183463	0.171306
OMEGA(2,1)	0.554610	NaN
OMEGA(2,2)	0.154408	0.167053

Boxcox

This section shows the effect of applying a Box-Cox transformation to the ETA variables in the base model.

The boxcox_parameters contains the estimated shape parameter (Lambda) and expected improvment in OFV for a Box-Cox transformation of the random effects.

	lambda	new_sd	old_sd
ETA(1)	-0.922083	0.182037	0.171306
ETA(2)	1.332800	0.166021	0.167053

Tdist

This section shows the effect of applying a t-distribution transformation to the ETA variables in the base model.

The tdist_parameters contains the estimated degrees of freedom and expected improvement in OFV for a t-distribution transformation of the random effects.

	df	new_sd	old_sd
ETA(1)	79.9997	0.168477	0.171306
ETA(2)	79.9986	0.166469	0.167053

Residual error

This section shows the effect of including extended residual error models in the base model.

The residual_error table contains the residual error models, resulting expected improvement in OFV, required additional model parameters as well as their estimates.

		dOFV	additional_parameters	parameters
DVID	model
1.0	dtbs	13.91	2	{'lambda': 0.242, 'zeta': 0.042}
	time_varying	8.03	2	{'sdeps_0-t0': 0.271, 'sdeps_t0-390': 0.956, '...
	tdist	5.53	1	{'df': 5.106}
	autocorrelation	3.34	1	{'half-life': 16.7}
	IIV_on_RUV	1.31	1	{'%CV': 21.772}
	power	0.03	1	{'delta_power': -0.037}

Covariate effects

This section evaluates the impact of supplied covariates.

The covariate_effects table shows the expected improvement when including covariates.

		dofv	coeff
parameter	covariate
ETA(1)	APGR	2.48793	-0.033334
	WGT	0.48218	0.052342
ETA(2)	APGR	0.59034	0.008371
	WGT	0.00887	-0.003273