Generate a SANTAObj containing all the splines model for individual and group time evolutions. Once all the splines representing individual and group evolutions are fitted, all time-points are back-projected (projected) and employed in subsequent analysis in place of the input measurements (functional approach). A grouping can be provided to separate individuals and compare trajectories: any number of groups can be provided, but comparision of group trajectories can only be executed between 2 groups.
Individual trajectories with less than 4 time-points are rejected due to constraints on
smooth.splinefitting (number of time-points < 4).Individual trajectories with less time-points than df are rejected due to constraints on
smooth.splinefitting (number of time-points < df).Rejected individual trajectories are not taken into account for mean curves calculations.
Arguments
- inputMatrix
data.frameof measurements for each IND x TIME as generated byget_ind_time_matrix. Rows are unique Individual IDs and columns unique measurement Time. Pairs of (IND,TIME) without a measurement are left as NA.- df
(float) Degree of freedom to employ for fitting the
smooth.spline- grouping
NA or a
data.framewith 2 columns (ind and group) listing as rows each unique Individual ID and the corresponding group membership, as generated byget_grouping. Default is NA for no groups.- verbose
(bool) If TRUE output the progress of fitting. Default is TRUE.
Value
A SANTAObj containing all the spline models with individual and group time evolutions, for further analysis.
Details:
The returned SANTAObj is structured as follow:
| SANTAObj | santaR object for futher analysis |
| SANTAObj$properties$df | input degree of freedom |
| SANTAObj$properties$CBand$status | Confidence Bands for group mean curve calculated (TRUE or FALSE) |
| SANTAObj$properties$CBand$nBoot | parameter, number or bootstrap rounds for calculation of the group mean curve confidence bands |
| SANTAObj$properties$CBand$alpha | parameter, confidence of the group mean curve band |
| SANTAObj$properties$pval.dist$status | p-value distance calculated (TRUE or FALSE) |
| SANTAObj$properties$pval.dist$nPerm | parameter, number of permutations for calculation of distance p-value |
| SANTAObj$properties$pval.dist$alpha | parameter, confidence on the bootstrapped p-value |
| SANTAObj$properties$pval.fit$status | p-value fitting calculated (TRUE or FALSE) |
| SANTAObj$properties$pval.fit$nPerm | parameter, number of permutations for calculation of fitting p-value |
| SANTAObj$properties$pval.fit$alpha | parameter, confidence on the bootstrapped p-value |
| SANTAObj$general$inputData | inputMatrix |
| SANTAObj$general$cleanData.in | only kept individuals INPUT values (equivalent to inputMatrix - rejected) |
| SANTAObj$general$cleanData.pred | only kept individuals PREDICTED values on Ind splines |
| SANTAObj$general$grouping | grouping vector given as input |
| SANTAObj$general$meanCurve | spline fit over all kept datapoint (cleanData.pred) | smooth.spline object |
| SANTAObj$general$pval.curveCorr | Pearson correlation coefficient between the two group curves, to detect highly correlated group shapes if required. |
| SANTAObj$general$pval.dist | p-value between groups based on distance between groupMeanCurves |
| SANTAObj$general$pval.dist.l | lower bound confidence interval on p-value |
| SANTAObj$general$pval.dist.u | upper bound confidence interval on p-value |
| SANTAObj$general$pval.fit | p-value between groups based on groupMeanCurves fitting |
| SANTAObj$general$pval.fit.l | lower bound confidence interval on p-value |
| SANTAObj$general$pval.fit.u | upper bound confidence interval on p-value |
| SANTAObj$groups | list of group information |
| SANTAObj$groups$rejectedInd | list of rejected individual (#tp < 4 or df) | data |
| SANTAObj$groups$curveInd | list of spline fit | smooth.spline object |
| SANTAObj$groups$groupMeanCurve | spline fit over groupData.pred | smooth.spline object |
| SANTAObj$groups$point.in | all group points INPUT values (x,y) [kept individuals] |
| SANTAObj$groups$point.pred | all group points PREDICTED values on Ind splines (x,y) |
| SANTAObj$groups$groupData.in | only individuals from this group INPUT value (IND x TIME) |
| SANTAObj$groups$groupData.pred | only individuals from this group PREDICTED values on Ind splines (x,y) |
See also
Other Analysis:
get_grouping(),
get_ind_time_matrix(),
santaR_CBand(),
santaR_auto_fit(),
santaR_auto_summary(),
santaR_plot(),
santaR_pvalue_dist(),
santaR_pvalue_fit(),
santaR_start_GUI()
Examples
## 56 measurements, 8 subjects, 7 unique time-points
Yi <- acuteInflammation$data$var_1
ind <- acuteInflammation$meta$ind
time <- acuteInflammation$meta$time
group <- acuteInflammation$meta$group
grouping <- get_grouping(ind, group)
inputMatrix <- get_ind_time_matrix(Yi, ind, time)
resultSANTAObj <- santaR_fit(inputMatrix, df=5, grouping=grouping, verbose=TRUE)