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Produce smooth error bar around multiple line graph using standard error in data frame

Time：11-15

Produce smooth error bar around multiple line graph using standard error available in the data frame. I already have the stadard error in the data frame so I could use data /- se.

Produce smooth error bar around multiple line graph using standard error available in the data frame. I already have the stadard error in the data frame so I could use data /- se.

data10 <- structure(list(Group = c("Visible", "Visible", "Visible", "Visible", 
"Visible", "Visible", "Visible", "Visible", "Visible", "Visible", 
"Visible", "Visible", "Visible", "Visible", "Visible", "Visible", 
"Visible", "Visible", "Visible", "Visible", "Visible", "Visible", 
"Visible", "Visible", "Visible", "Visible", "Visible", "Visible", 
"Visible", "Visible", "Visible", "Visible", "Remembered", "Remembered", 
"Remembered", "Remembered", "Remembered", "Remembered", "Remembered", 
"Remembered", "Remembered", "Remembered", "Remembered", "Remembered", 
"Remembered", "Remembered", "Remembered", "Remembered", "Remembered", 
"Remembered", "Remembered", "Remembered", "Remembered", "Remembered", 
"Remembered", "Remembered", "Remembered", "Remembered", "Remembered", 
"Remembered", "Remembered", "Remembered", "Remembered", "Remembered", 
"Visible", "Visible", "Visible", "Visible", "Visible", "Visible", 
"Visible", "Visible", "Visible", "Visible", "Visible", "Visible", 
"Visible", "Visible", "Visible", "Visible", "Visible", "Visible", 
"Visible", "Visible", "Visible", "Visible", "Visible", "Visible", 
"Visible", "Visible", "Visible", "Visible", "Visible", "Visible", 
"Visible", "Visible", "Remembered", "Remembered", "Remembered", 
"Remembered", "Remembered", "Remembered", "Remembered", "Remembered", 
"Remembered", "Remembered", "Remembered", "Remembered", "Remembered", 
"Remembered", "Remembered", "Remembered", "Remembered", "Remembered", 
"Remembered", "Remembered", "Remembered", "Remembered", "Remembered", 
"Remembered", "Remembered", "Remembered", "Remembered", "Remembered", 
"Remembered", "Remembered", "Remembered", "Remembered"), Condition = c("CEN", 
"CEN", "CEN", "CEN", "CEN", "CEN", "CEN", "CEN", "CEN", "CEN", 
"CEN", "CEN", "CEN", "CEN", "CEN", "CEN", "IPS", "IPS", "IPS", 
"IPS", "IPS", "IPS", "IPS", "IPS", "IPS", "IPS", "IPS", "IPS", 
"IPS", "IPS", "IPS", "IPS", "CEN", "CEN", "CEN", "CEN", "CEN", 
"CEN", "CEN", "CEN", "CEN", "CEN", "CEN", "CEN", "CEN", "CEN", 
"CEN", "CEN", "IPS", "IPS", "IPS", "IPS", "IPS", "IPS", "IPS", 
"IPS", "IPS", "IPS", "IPS", "IPS", "IPS", "IPS", "IPS", "IPS", 
"CEN", "CEN", "CEN", "CEN", "CEN", "CEN", "CEN", "CEN", "CEN", 
"CEN", "CEN", "CEN", "CEN", "CEN", "CEN", "CEN", "IPS", "IPS", 
"IPS", "IPS", "IPS", "IPS", "IPS", "IPS", "IPS", "IPS", "IPS", 
"IPS", "IPS", "IPS", "IPS", "IPS", "CEN", "CEN", "CEN", "CEN", 
"CEN", "CEN", "CEN", "CEN", "CEN", "CEN", "CEN", "CEN", "CEN", 
"CEN", "CEN", "CEN", "IPS", "IPS", "IPS", "IPS", "IPS", "IPS", 
"IPS", "IPS", "IPS", "IPS", "IPS", "IPS", "IPS", "IPS", "IPS", 
"IPS"), test = c("Pre-test", "Pre-test", "Pre-test", "Pre-test", 
"Pre-test", "Pre-test", "Pre-test", "Pre-test", "Post-test", 
"Post-test", "Post-test", "Post-test", "Post-test", "Post-test", 
"Post-test", "Post-test", "Pre-test", "Pre-test", "Pre-test", 
"Pre-test", "Pre-test", "Pre-test", "Pre-test", "Pre-test", "Post-test", 
"Post-test", "Post-test", "Post-test", "Post-test", "Post-test", 
"Post-test", "Post-test", "Pre-test", "Pre-test", "Pre-test", 
"Pre-test", "Pre-test", "Pre-test", "Pre-test", "Pre-test", "Post-test", 
"Post-test", "Post-test", "Post-test", "Post-test", "Post-test", 
"Post-test", "Post-test", "Pre-test", "Pre-test", "Pre-test", 
"Pre-test", "Pre-test", "Pre-test", "Pre-test", "Pre-test", "Post-test", 
"Post-test", "Post-test", "Post-test", "Post-test", "Post-test", 
"Post-test", "Post-test", "Pre-test", "Pre-test", "Pre-test", 
"Pre-test", "Pre-test", "Pre-test", "Pre-test", "Pre-test", "Post-test", 
"Post-test", "Post-test", "Post-test", "Post-test", "Post-test", 
"Post-test", "Post-test", "Pre-test", "Pre-test", "Pre-test", 
"Pre-test", "Pre-test", "Pre-test", "Pre-test", "Pre-test", "Post-test", 
"Post-test", "Post-test", "Post-test", "Post-test", "Post-test", 
"Post-test", "Post-test", "Pre-test", "Pre-test", "Pre-test", 
"Pre-test", "Pre-test", "Pre-test", "Pre-test", "Pre-test", "Post-test", 
"Post-test", "Post-test", "Post-test", "Post-test", "Post-test", 
"Post-test", "Post-test", "Pre-test", "Pre-test", "Pre-test", 
"Pre-test", "Pre-test", "Pre-test", "Pre-test", "Pre-test", "Post-test", 
"Post-test", "Post-test", "Post-test", "Post-test", "Post-test", 
"Post-test", "Post-test"), trial = c(1, 2, 3, 4, 5, 6, 7, 8, 
9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 
11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 
13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 
15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 
1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 
3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 
5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16), Variables = c("Eye movement time", 
"Eye movement time", "Eye movement time", "Eye movement time", 
"Eye movement time", "Eye movement time", "Eye movement time", 
"Eye movement time", "Eye movement time", "Eye movement time", 
"Eye movement time", "Eye movement time", "Eye movement time", 
"Eye movement time", "Eye movement time", "Eye movement time", 
"Eye movement time", "Eye movement time", "Eye movement time", 
"Eye movement time", "Eye movement time", "Eye movement time", 
"Eye movement time", "Eye movement time", "Eye movement time", 
"Eye movement time", "Eye movement time", "Eye movement time", 
"Eye movement time", "Eye movement time", "Eye movement time", 
"Eye movement time", "Eye movement time", "Eye movement time", 
"Eye movement time", "Eye movement time", "Eye movement time", 
"Eye movement time", "Eye movement time", "Eye movement time", 
"Eye movement time", "Eye movement time", "Eye movement time", 
"Eye movement time", "Eye movement time", "Eye movement time", 
"Eye movement time", "Eye movement time", "Eye movement time", 
"Eye movement time", "Eye movement time", "Eye movement time", 
"Eye movement time", "Eye movement time", "Eye movement time", 
"Eye movement time", "Eye movement time", "Eye movement time", 
"Eye movement time", "Eye movement time", "Eye movement time", 
"Eye movement time", "Eye movement time", "Eye movement time", 
"Hand movement time", "Hand movement time", "Hand movement time", 
"Hand movement time", "Hand movement time", "Hand movement time", 
"Hand movement time", "Hand movement time", "Hand movement time", 
"Hand movement time", "Hand movement time", "Hand movement time", 
"Hand movement time", "Hand movement time", "Hand movement time", 
"Hand movement time", "Hand movement time", "Hand movement time", 
"Hand movement time", "Hand movement time", "Hand movement time", 
"Hand movement time", "Hand movement time", "Hand movement time", 
"Hand movement time", "Hand movement time", "Hand movement time", 
"Hand movement time", "Hand movement time", "Hand movement time", 
"Hand movement time", "Hand movement time", "Hand movement time", 
"Hand movement time", "Hand movement time", "Hand movement time", 
"Hand movement time", "Hand movement time", "Hand movement time", 
"Hand movement time", "Hand movement time", "Hand movement time", 
"Hand movement time", "Hand movement time", "Hand movement time", 
"Hand movement time", "Hand movement time", "Hand movement time", 
"Hand movement time", "Hand movement time", "Hand movement time", 
"Hand movement time", "Hand movement time", "Hand movement time", 
"Hand movement time", "Hand movement time", "Hand movement time", 
"Hand movement time", "Hand movement time", "Hand movement time", 
"Hand movement time", "Hand movement time", "Hand movement time", 
"Hand movement time"), Eye_Mx = c(1.150583333, 1.273916667, 1.213083333, 
1.065166667, 1.2373, 1.19925, 0.93675, 0.950833333, 0.616916667, 
0.440416667, 0.598083333, 0.618583333, 0.693545455, 0.667583333, 
0.873666667, 0.51825, 1.220454545, 1.034583333, 0.874583333, 
1.015166667, 0.532222222, 0.714454545, 0.905583333, 0.898333333, 
0.641666667, 0.787666667, 0.609833333, 0.623583333, 0.69925, 
0.7188, 0.61725, 0.661166667, 1.349, 1.585416667, 1.0145, 1.201090909, 
0.810545455, 0.591090909, 1.1416, 0.697166667, 0.431166667, 0.804583333, 
0.289666667, 0.63875, 0.46825, 0.633, 0.418833333, 0.691166667, 
1.219125, 0.7033, 0.524666667, 0.724818182, 0.648583333, 0.639181818, 
0.596583333, 0.509416667, 0.576272727, 0.483222222, 0.388222222, 
0.647, 0.42575, 0.269818182, 0.488333333, 0.5903, 1.869083333, 
2.066181818, 2.124166667, 2.31525, 2.0943, 1.93625, 1.786916667, 
1.922583333, 1.470833333, 1.421454545, 1.519083333, 1.508833333, 
1.575909091, 1.5135, 1.8025, 1.541, 1.800454545, 1.888666667, 
1.85575, 2.201666667, 1.55725, 1.7781, 1.748, 1.767583333, 1.489333333, 
1.4259, 1.436916667, 1.5855, 1.535666667, 1.4013, 1.3855, 1.356666667, 
1.852888889, 2.463636364, 2.031, 2.195727273, 1.804454545, 1.709090909, 
2.1938, 1.97625, 1.256833333, 1.704363636, 1.418083333, 1.371166667, 
1.459166667, 1.46725, 1.183666667, 1.407, 2.348625, 1.8981, 1.973583333, 
1.746727273, 1.6805, 1.963, 1.68075, 1.872583333, 1.345636364, 
1.339222222, 1.311222222, 1.316833333, 1.215833333, 1.053636364, 
1.415916667, 1.2292), sd = c(0.948671172, 0.678775831, 0.820965004, 
0.771358286, 1.11350558, 0.598444974, 0.794668727, 0.824723627, 
0.481933503, 0.314103185, 0.469586754, 0.576648697, 0.629203681, 
0.528873667, 0.975212642, 0.406696922, 0.986302019, 0.821480975, 
0.776634401, 0.804389643, 0.52690957, 0.881839936, 0.881676756, 
0.842954149, 0.49820502, 0.551171205, 0.611370269, 0.630794947, 
0.605911653, 0.612136659, 0.504005614, 0.478993231, 0.896792758, 
1.545713396, 1.479810742, 1.481512366, 1.016337185, 0.827241616, 
1.987092303, 0.874371549, 0.557526165, 1.312183015, 0.163762763, 
1.081580084, 0.682258832, 0.99675364, 0.582176455, 1.069035235, 
1.352635886, 1.003522136, 0.705413397, 0.93395362, 0.764277848, 
0.989686599, 0.875251492, 0.582424316, 0.618786084, 0.971365119, 
0.4453251, 1.057255968, 0.710771044, 0.157439397, 0.584064339, 
0.966582301, 0.807429305, 0.578682092, 0.911954428, 1.146678771, 
0.977409848, 0.7173858, 0.692368328, 0.84760684, 0.426626052, 
0.392027133, 0.463031406, 0.346331904, 0.435984278, 0.625301164, 
0.733525794, 0.468399014, 0.911551574, 0.845252338, 0.560227896, 
1.191183013, 0.503701088, 0.686482249, 0.812501692, 0.649220856, 
0.448065201, 0.520082782, 0.465629478, 0.601450142, 0.498518229, 
0.432112652, 0.422273393, 0.374147354, 0.631002663, 1.659917846, 
1.024954525, 1.202822771, 0.652806306, 0.768222032, 1.742846509, 
0.782477781, 0.398411581, 0.98639944, 0.580826286, 0.781519247, 
0.683742619, 0.717473487, 0.26632937, 0.748351886, 1.884740371, 
0.875399141, 0.661320505, 0.703044393, 0.49535084, 0.954243365, 
0.645801986, 1.293963499, 0.649359573, 0.623769945, 0.256283426, 
0.8611224, 0.495113363, 0.158687285, 0.522609442, 0.635988959
), se = c(0.273857778, 0.195945704, 0.236992183, 0.222671957, 
0.352121382, 0.172756183, 0.229401102, 0.238077204, 0.139122219, 
0.090673779, 0.135558019, 0.16646414, 0.189712048, 0.152672677, 
0.281519641, 0.117403289, 0.297381248, 0.237141131, 0.22419504, 
0.232207288, 0.175636523, 0.265884745, 0.254518156, 0.243339902, 
0.143819401, 0.159109422, 0.176487395, 0.182094816, 0.174911628, 
0.193574608, 0.145493889, 0.138273435, 0.298930919, 0.446209023, 
0.467957245, 0.446692786, 0.306437191, 0.249422732, 0.62837376, 
0.252409325, 0.160943941, 0.378794609, 0.047274238, 0.312225276, 
0.19695116, 0.287737991, 0.168059866, 0.30860389, 0.478229004, 
0.317341563, 0.203635307, 0.281597612, 0.220628011, 0.298401737, 
0.252663342, 0.168131418, 0.186571024, 0.323788373, 0.1484417, 
0.305203509, 0.205181927, 0.047469764, 0.168604852, 0.305660162, 
0.233084763, 0.174479216, 0.263258567, 0.331017649, 0.309084133, 
0.207091442, 0.19986952, 0.244683019, 0.123156333, 0.118200628, 
0.133665654, 0.099977409, 0.131454206, 0.180508898, 0.211750657, 
0.135215148, 0.274843141, 0.244003332, 0.161723863, 0.343864917, 
0.178085227, 0.217084748, 0.244978478, 0.187413918, 0.129345282, 
0.164464616, 0.134415652, 0.173623701, 0.143909817, 0.136646019, 
0.121899828, 0.108007038, 0.210334221, 0.500484062, 0.32411908, 
0.362664711, 0.196828507, 0.231627658, 0.551136458, 0.225881879, 
0.115011517, 0.297410621, 0.167670106, 0.225605174, 0.197379493, 
0.207116755, 0.076882667, 0.216030581, 0.666356349, 0.276825515, 
0.190906786, 0.21197586, 0.14299547, 0.2877152, 0.186426975, 
0.373535087, 0.195789278, 0.207923315, 0.085427809, 0.248584625, 
0.142926917, 0.047846017, 0.150864351, 0.201117368), ci = c(0.602756906, 
0.431273588, 0.521616278, 0.490097673, 0.796553907, 0.380233796, 
0.504908421, 0.524004393, 0.306205939, 0.199571642, 0.298361189, 
0.366385102, 0.422704785, 0.336030297, 0.619620551, 0.258402896, 
0.662606712, 0.52194411, 0.493449956, 0.511084796, 0.405018549, 
0.59242813, 0.560190685, 0.535587514, 0.316544368, 0.350197476, 
0.388446137, 0.400787988, 0.384977898, 0.437896186, 0.320229889, 
0.304337779, 0.689335936, 0.982099437, 1.058592834, 0.99529355, 
0.682784611, 0.555748479, 1.421480202, 0.555549178, 0.354235225, 
0.833721312, 0.104049895, 0.6872032, 0.433486581, 0.633307048, 
0.369897272, 0.679232583, 1.1308319, 0.71787649, 0.448198289, 
0.627438579, 0.485598977, 0.664880504, 0.556108267, 0.370054755, 
0.415706148, 0.746657327, 0.342307174, 0.671748394, 0.451602376, 
0.105769226, 0.371096776, 0.691451324, 0.513016105, 0.388763919, 
0.5794282, 0.728564932, 0.699196885, 0.455805192, 0.439909848, 
0.538543693, 0.271065261, 0.263367411, 0.29419612, 0.220048794, 
0.292898224, 0.397297405, 0.466060055, 0.297606535, 0.61238868, 
0.537047714, 0.355951823, 0.756841578, 0.421104648, 0.491079817, 
0.545846064, 0.412495252, 0.284687047, 0.37204481, 0.295846856, 
0.382143188, 0.316743371, 0.30911477, 0.268299713, 0.237721887, 
0.485031584, 1.115147982, 0.733208298, 0.808067333, 0.438561244, 
0.516098584, 1.246757287, 0.497162663, 0.253138642, 0.66267216, 
0.369039416, 0.49655364, 0.434429334, 0.455860905, 0.169217609, 
0.475480104, 1.575682382, 0.626222821, 0.420183003, 0.47231165, 
0.314730908, 0.641069416, 0.410323006, 0.822145184, 0.436245697, 
0.479472024, 0.19699688, 0.54713107, 0.314580023, 0.106607569, 
0.332050198, 0.454959094)), class = c("spec_tbl_df", "tbl_df", 
"tbl", "data.frame"), row.names = c(NA, -128L), spec = structure(list(
    cols = list(Group = structure(list(), class = c("collector_character", 
    "collector")), Condition = structure(list(), class = c("collector_character", 
    "collector")), test = structure(list(), class = c("collector_character", 
    "collector")), trial = structure(list(), class = c("collector_double", 
    "collector")), Variables = structure(list(), class = c("collector_character", 
    "collector")), Eye_Mx = structure(list(), class = c("collector_double", 
    "collector")), sd = structure(list(), class = c("collector_double", 
    "collector")), se = structure(list(), class = c("collector_double", 
    "collector")), ci = structure(list(), class = c("collector_double", 
    "collector"))), default = structure(list(), class = c("collector_guess", 
    "collector")), skip = 1), class = "col_spec"))

p <- ggplot(data10, aes(x = trial, y = Eye_Mx))   
   geom_line(aes(color = Variables, linetype = Variables), lwd=1.2)   
   scale_color_manual(values = c("darkred", "steelblue"))   facet_grid(Condition ~ Group)  theme_bw()   xlab("Trial Pre- / Post-test")   ylab("Hand and Eye Movement time (s)")  
   scale_x_continuous(limits = c(1,16), breaks = seq(1,16,1))   theme(axis.text.x = element_text(size = 10,face="bold", angle = 90),#, angle = 10, hjust = .5, vjust = .5),
                                                                      axis.text.y = element_text(size = 10, face = "bold"),
                                                                      axis.title.y = element_text(vjust= 1.8, size = 16),
                                                                      axis.title.x = element_text(vjust= -0.5, size = 16),
                                                                      axis.title = element_text(face = "bold"))    theme(legend.position="top") 
   geom_vline(xintercept=8.5, linetype="dashed", color = "black", size=1.5) 
 
 p   guides(fill=guide_legend(title="Variables:"))   theme(legend.text=element_text(size=14),legend.title=element_text(size=14) )  
   theme(strip.text = element_text(face="bold", size=12))

CodePudding user response：

Is it necessary to use your data? You could simply use geom_smooth and set se=TRUE.

p <- ggplot(data10, aes(x = trial, y = Eye_Mx))   
  geom_line(aes(color = Variables, linetype = Variables), lwd=1.2)   
  scale_color_manual(values = c("darkred", "steelblue"))   facet_grid(Condition ~ Group)  theme_bw()   xlab("Trial Pre- / Post-test")   ylab("Hand and Eye Movement time (s)")  
  scale_x_continuous(limits = c(1,16), breaks = seq(1,16,1))   theme(axis.text.x = element_text(size = 10,face="bold", angle = 90),#, angle = 10, hjust = .5, vjust = .5),
                                                                     axis.text.y = element_text(size = 10, face = "bold"),
                                                                     axis.title.y = element_text(vjust= 1.8, size = 16),
                                                                     axis.title.x = element_text(vjust= -0.5, size = 16),
                                                                     axis.title = element_text(face = "bold"))    theme(legend.position="top") 
  geom_vline(xintercept=8.5, linetype="dashed", color = "black", size=1.5)  
  geom_smooth(method="loess", se=TRUE, fullrange=FALSE, level=0.95)

p   guides(fill=guide_legend(title="Variables:"))   theme(legend.text=element_text(size=14),legend.title=element_text(size=14) )  
  theme(strip.text = element_text(face="bold", size=12))

CodePudding user response：

As your standard errors are already included in your data you could add a confidence interval around you lines via geom_ribbon like so:

library(ggplot2)

ggplot(data10, aes(x = trial, y = Eye_Mx))   
  geom_line(aes(color = Variables, linetype = Variables), lwd=1.2)   
  geom_ribbon(aes(ymin = Eye_Mx - 1.96 * se, ymax = Eye_Mx   1.96 * se, fill = Variables), alpha = .3)  
  scale_color_manual(values = c("darkred", "steelblue"))   facet_grid(Condition ~ Group)  theme_bw()   xlab("Trial Pre- / Post-test")   ylab("Hand and Eye Movement time (s)")  
  scale_x_continuous(limits = c(1,16), breaks = seq(1,16,1))   theme(axis.text.x = element_text(size = 10,face="bold", angle = 90),#, angle = 10, hjust = .5, vjust = .5),
                                                                     axis.text.y = element_text(size = 10, face = "bold"),
                                                                     axis.title.y = element_text(vjust= 1.8, size = 16),
                                                                     axis.title.x = element_text(vjust= -0.5, size = 16),
                                                                     axis.title = element_text(face = "bold"))    theme(legend.position="top") 
  geom_vline(xintercept=8.5, linetype="dashed", color = "black", size=1.5)  
  guides(fill=guide_legend(title="Variables:"))   theme(legend.text=element_text(size=14),legend.title=element_text(size=14) )  
  theme(strip.text = element_text(face="bold", size=12))

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