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## Figure 1
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# Status (excluded, not excluded)
nv_status = lm(success ~  EPR_STATUS_EXCL + EPR_GROUPSIZE + POP_LOG_LAG_EXT + GDPPC_LOG_LAG_EXT + VDEM_POLYARCHY_LAG + VDEM_PHYSINT_LAG + EPR_TEK_EGIP + EPR_DOWNGRADED5 + HORIZ_INEQ + NVYEARS + I(NVYEARS^2) + I(NVYEARS^3) + VYEARS + I(VYEARS^2) + I(VYEARS^3) , data= EBCR_EPR_NAVCO2[EBCR_EPR_NAVCO2$INIT_NV_ONSET==1,])  
v_status = lm(success ~  EPR_STATUS_EXCL + EPR_GROUPSIZE + POP_LOG_LAG_EXT + GDPPC_LOG_LAG_EXT  + VDEM_POLYARCHY_LAG + VDEM_PHYSINT_LAG + EPR_TEK_EGIP + EPR_DOWNGRADED5 + HORIZ_INEQ + NVYEARS + I(NVYEARS^2) + I(NVYEARS^3) + VYEARS + I(VYEARS^2) + I(VYEARS^3) , data= EBCR_EPR_NAVCO2[EBCR_EPR_NAVCO2$INIT_V_ONSET==1,])  

preds_nv = ggpredict(nv_status, terms = c("EPR_STATUS_EXCL"))
preds_nv$tactic = "Non-violent"
preds_v = ggpredict(v_status, terms = c("EPR_STATUS_EXCL"))
preds_v$tactic = "Violent"

preds = rbind(preds_nv, preds_v)
preds$tactic <- factor(preds$tactic, levels = c("Violent", "Non-violent"))
preds$Status = "Minority/disadvantaged"
preds$Status[preds$x==0] = "Majority/dominant"

xtable(preds[,-1], digits=2)
preds = as.data.frame(preds)
preds$Status = as.factor(preds$Status)

status = ggplot(preds, aes(x = tactic, y = predicted, group=Status)) +
  geom_line(aes(color=Status))+ geom_errorbar(aes(color = Status), width = 0, ymin=preds$conf.low, ymax=preds$conf.high)+
  geom_point(aes(color=Status, shape=Status), size=3) + ylim(-0.1,0.5) +  theme_bw() +
  scale_colour_grey(start = 0.1, end = 0.65) + geom_hline(yintercept=0, linetype="dashed")+
  ylab("Pr(Campaign Success)") + xlab("Tactic") +ggtitle("(A) Group Status") +
  theme(legend.position="none")

## Size (above and below the mean of the distribution)
EBCR_EPR_NAVCO2$small_size = NA
EBCR_EPR_NAVCO2$small_size[EBCR_EPR_NAVCO2$EPR_GROUPSIZE < mean(EBCR_EPR_NAVCO2$EPR_GROUPSIZE, na.rm=T)] = 1
EBCR_EPR_NAVCO2$small_size[EBCR_EPR_NAVCO2$EPR_GROUPSIZE >= mean(EBCR_EPR_NAVCO2$EPR_GROUPSIZE, na.rm=T)] = 0

nv_size = lm(success ~  small_size  + POP_LOG_LAG_EXT + GDPPC_LOG_LAG_EXT  + VDEM_POLYARCHY_LAG + VDEM_PHYSINT_LAG + EPR_TEK_EGIP + EPR_DOWNGRADED5 + HORIZ_INEQ + NVYEARS + I(NVYEARS^2) + I(NVYEARS^3) + VYEARS + I(VYEARS^2) + I(VYEARS^3) , data= EBCR_EPR_NAVCO2[EBCR_EPR_NAVCO2$INIT_NV_ONSET==1,])  
v_size = lm(success ~  small_size  + POP_LOG_LAG_EXT + GDPPC_LOG_LAG_EXT + VDEM_POLYARCHY_LAG + VDEM_PHYSINT_LAG + EPR_TEK_EGIP + EPR_DOWNGRADED5 + HORIZ_INEQ + NVYEARS + I(NVYEARS^2) + I(NVYEARS^3) + VYEARS + I(VYEARS^2) + I(VYEARS^3) , data= EBCR_EPR_NAVCO2[EBCR_EPR_NAVCO2$INIT_V_ONSET==1,])  

preds_nv = ggpredict(nv_size, terms = c("small_size"))
preds_nv$tactic = "Non-violent"
preds_v = ggpredict(v_size, terms = c("small_size"))
preds_v$tactic = "Violent"

preds = rbind(preds_nv, preds_v)
preds$tactic <- factor(preds$tactic, levels = c("Violent", "Non-violent"))
preds$Status = "Minority/disadvantaged"
preds$Status[preds$x==0] = "Majority/dominant"

preds = as.data.frame(preds)
preds$Status = as.factor(preds$Status)

xtable(preds[,-1], digits=2)

size = ggplot(preds, aes(x = tactic, y = predicted, group=Status)) +
  geom_line(aes(color=Status))+ geom_errorbar(aes(color = Status), width = 0, ymin=preds$conf.low, ymax=preds$conf.high)+
  geom_point(aes(color=Status, shape=Status), size=3) + ylim(-0.1,0.5) + theme_bw() +
  #scale_color_manual(values=c("#E69F00", "#56B4E9")) + geom_hline(yintercept=0, linetype="dashed")+
  scale_colour_grey(start = 0.1, end = 0.65) + geom_hline(yintercept=0, linetype="dashed")+
  ylab("Pr(Campaign Success)") + xlab("Tactic")  +ggtitle("(B) Group Size") +
  theme(legend.position="none")

fig1 = grid_arrange_shared_legend(status, size, ncol = 2, nrow = 1)
ggsave(file="Figures/fig_1.pdf", fig1, width=8, height=4)