Description Usage Arguments Details Value Author(s) References See Also Examples

This function implements the generalized logistic analysis introduced in Verboon & Peters (2017). This analysis fits a logistic function (i.e. a sigmoid) to a data series. This is useful when analysing single case designs. The function enables easy customization of the main plot elements and easy saving of the plot with anti-aliasing. `ggGenLogPlot`

does most of the plotting, and can be useful when trying to figure out sensible starting and boundary/constraint values. `genlogCompleteStartValues`

tries to compute sensible starting and boundary/constraint values based on the data.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 | ```
genlog(data,
timeVar = 1,
yVar = 2,
phaseVar = NULL,
baselineMeasurements = NULL,
yRange = NULL,
startInflection = NULL,
startBase = NULL,
startTop = NULL,
startGrowthRate = NULL,
startV = 1,
inflectionPointBounds = NULL,
growthRateBounds = c(-2, 2),
baseMargin = c(0, 3),
topMargin = c(-3, 0),
baseBounds = NULL,
topBounds = NULL,
vBounds = c(1, 1),
changeDelay = 4,
colors = list(bottomBound = viridis(4)[4],
topBound = viridis(40)[37],
curve = viridis(4)[3],
mid = viridis(4)[2],
intervention = viridis(4)[1],
points = "black",
outsideRange = "black"),
alphas = list(outsideRange = .2,
bounds = 0,
points = .5,
mid = 0),
theme = theme_minimal(),
pointSize = 2,
lineSize = 0.5,
yBreaks = NULL,
initialValuesLineType = "blank",
curveSizeMultiplier = 2,
showPlot = TRUE,
plotLabs = NULL,
outputFile = NULL,
outputWidth = 16,
outputHeight = 16,
ggsaveParams = list(units = "cm",
dpi = 300,
type = "cairo"),
maxiter = NULL)
``` |

`data` |
The dataframe containing the variables for the analysis. |

`timeVar` |
The name of the variable containing the measurement moments (or an index of measurement moments). An index can also be specified, and assumed to be 1 if omitted. |

`yVar` |
The name of the dependent variable. An index can also be specified, and assumed to be 2 if omitted. |

`phaseVar` |
The variable containing the phase of each measurement. Note that this normally should only have two possible values. |

`baselineMeasurements` |
If no phaseVar is specified, |

`yRange` |
This can be used to manually specify the possible values that the dependent variable can take. If no |

`startInflection, startBase, startTop, startGrowthRate, startV` |
The starting values used when estimating the sigmoid using |

`inflectionPointBounds, growthRateBounds, baseMargin, topMargin, baseBounds, topBounds, vBounds` |
These values specify constraints to respect when estimating the parameters of the sigmoid function using |

`changeDelay` |
The number of measurements to add to the intervention moment when setting the initial value for the inflection point. |

`colors` |
The colors to use for the different plot elements. |

`alphas` |
The alpha values (transparency, or rather, 'obliqueness', with 0 indicating full transparency and 1 indicating full visibility) to use for the different plot elements. |

`theme` |
The theme to use in the plot. |

`pointSize,lineSize ` |
The sizes of points and lines in the plot. |

`yBreaks` |
If |

`initialValuesLineType` |
The line type to use for the initial values; by default set to |

`curveSizeMultiplier` |
A multiplyer for the curve size compared to the other lines (e.g. specify '2' to have a curve of twice the size). |

`showPlot` |
Whether to show the plot or not. |

`plotLabs` |
A list with arguments to the |

`outputFile` |
If not |

`outputWidth, outputHeight` |
The dimensions of the plot when saving it (in units specified in |

`ggsaveParams` |
The parameters to use when saving the plot, passed on to |

`maxiter` |
The maximum number of iterations used by |

For details, see Verboon & Peters (2017).

Mainly, this function prints its results, but it also returns them in an object containing three lists:

`input` |
The arguments specified when calling the function |

`intermediate` |
Intermediat objects and values |

`output` |
The results such as the plot. |

Peter Verboon & Gjalt-Jorn Peters (both at the Open University of the Netherlands)

Maintainer: Gjalt-Jorn Peters <gjalt-jorn@userfriendlyscience.com>

Verboon, P. & Peters, G.-J. Y. (2018) Applying the generalised logistic model in single case designs: modelling treatment-induced shifts. *PsyArXiv* https://doi.org/10.17605/osf.io/ad5eh

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