ggplot with error bars differentiated by shape of points - r

Question

Getting an error message that reads ' Error: All unnamed arguments must be length 1'. I am trying to differentiate my line by the shape of the point and I keep getting the errors above. I want to use all solid lines but differentiated by shape. The journal I want to public my work requires black and white instead of color
The plot I want to modify:
tgc <- structure(
list(
GROUP = structure(
c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L),
.Label = c("LLL", "LRL", "RLR", "RRR"),
class = "factor"
),
condition = structure(
c(1L, 1L, 2L, 2L, 3L, 3L, 1L, 1L, 2L, 2L, 3L, 3L, 1L, 1L, 2L, 2L, 3L, 3L, 1L, 1L, 2L, 2L, 3L, 3L),
.Label = c("Midline", "No Midline crossing", "Midline crossing"),
class = "factor"
),
names = structure(
c(1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L),
.Label = c("102", "104"),
class = "factor"
),
Trial_type = structure(
c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L),
.Label = c("retention", "transfer"),
class = "factor"
),
Training = structure(
c(2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L),
.Label = c("right", "left"),
class = "factor"
),
N = c(8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8),
NormalizedJerk = c(2060.1571177375, 1092.701687475,
2981.812368875, 1508.28547575, 2089.925186675, 1269.6704558875,
1391.97364445, 914.38364425, 3900.4119165625, 2335.7186722875,
4015.516784, 2563.16723475, 1411.2016892375, 847.952527975,
1853.413925525, 1394.847246875, 6830.81906275, 3915.019566375,
2310.5893110125, 1023.1702538875, 1340.4653657625, 765.2752940875,
5617.967587, 1705.629421875
),
sd = c(1507.9737264907, 946.522319997832,
1403.37144167604, 813.034284948276, 1383.95826055979, 915.414811222361,
580.358119711544, 361.141583497209, 3283.59638643298, 1471.60790379469,
1178.5979495842, 806.56121914288, 701.001824354642, 324.415375522303,
2103.42765701483, 1208.14874080532, 4671.80701687463, 2861.85154237875,
2130.92970547315, 813.649686635084, 489.544827982279, 256.250905151245,
5305.91963495324, 878.475841087918
),
se = c(533.14922392636,
334.646175507445, 496.166731466336, 287.451028112041, 489.303135460484,
323.648010306967, 205.187580982353, 127.682831329662, 1160.9266357632,
520.291964010475, 416.697301221774, 285.16245374901, 247.841571812654,
114.6981559765, 743.673980005258, 427.145083652716, 1651.73321101347,
1011.8173161826, 753.397422485958, 287.668605464989, 173.080233780536,
90.5983763588182, 1875.92587715314, 310.588112170911
),
ci = c(1260.69758461414,
791.31246230768, 1173.24788605882, 679.713672219011, 1157.01806049025,
765.305934151606, 485.191530116531, 301.92191947415, 2745.15527724569,
1230.29499600801, 985.332544042271, 674.302053778614, 586.052191261077,
271.218041235005, 1758.50952839896, 1010.03762375384, 3905.72840792368,
2392.56776402689, 1781.50181629779, 680.228160904389, 409.269718268804,
214.231117892992, 4435.85982330679, 734.424182295757
)
),
row.names = c(NA, -24L),
class = "data.frame"
)
tgc <- summarySE(
data10,
measurevar = "NormalizedJerk",
groupvars = c("GROUP", "condition", "names","Trial_type", "Training")
)
pd <- position_dodge2(0.2)
p <-ggplot(
gc,
aes(
names,
NormalizedJerk,
group = interaction(Training, Trial_type),
color = interaction(Training, Trial_type),
linetype = interaction(Training, Trial_type),
shape = Training
)
) +
geom_errorbar(
aes(ymin = NormalizedJerk - se, ymax = NormalizedJerk + se),
width = .3,
position = pd
) +
geom_line(
position = pd,
size = 1
) +
geom_point(
aes(shape = Training),
position = pd,
size = 1
)+
scale_colour_manual(
name = "Experimental group",
values = c("#999999","#999999","#000000","#000000")
labels = c("RRR","LLL","LRL","RLR")
) +
scale_shape_manual(
name = "Experimental group",
values = c("19","18","19","18")
) +
scale_linetype_manual(
name = "Experimental group",
values = c("solid","solid","solid","solid"),
labels = c("RRR","LLL","LRL","RLR")
) +
theme_bw() +
facet_wrap(.~condition) +
theme(
axis.title.y = element_text(vjust= 1.8, size = 14),
axis.title.x = element_text(vjust= -0.5, size = 14),
axis.title = element_text(face = "bold")
) +
xlab("Block of trials") +
ylab("Normalized Jerk")
p +
scale_x_discrete(
breaks=c("102","104"),
labels=c("Pretest","Posttest")
)

Answer 1

I modified your code a little. Thanks to Nic3500 for formatting the code.
You needed to add the same labels to the shape manual override as the others and turn the error bar legend off. I also increased the size of the legend because the default seems too small when showing different line types.
ggplot(tgc,
aes(
names,
NormalizedJerk,
group = interaction(Training, Trial_type),
color = interaction(Training, Trial_type),
linetype = interaction(Training, Trial_type),
shape = Training
)
) +
geom_errorbar(aes(ymin=NormalizedJerk-se, ymax=NormalizedJerk+se),
show.legend=FALSE, # <- here
width=.3, position=pd) +
geom_line(position=pd, size = 1) +
geom_point(position=pd, size= 2) +
scale_colour_manual(name = "Experimental group",
values=c("#999999","#999999","#000000","#000000"),
labels=c("RRR","LLL","LRL","RLR")) +
scale_shape_manual(name = "Experimental group", values=c(19,18,19,18),
labels=c("RRR","LLL","LRL","RLR")) + # <- here
scale_linetype_manual(name = "Experimental group",
values=c("solid","dashed","solid","dashed"),
labels=c("RRR","LLL","LRL","RLR")) +
theme_bw()+
facet_wrap(.~condition) +
theme(axis.title.y = element_text(vjust= 1.8, size = 14),
axis.title.x = element_text(vjust= -0.5, size = 14),
axis.title = element_text(face = "bold"),
legend.key.width = grid::unit(1.25, "cm")) + # <- here
xlab("Block of trials") + ylab("Normalized Jerk")