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This vignette shows model engines that
DAGassist
has been verified to work with and provides
concrete usage examples. The list is illustrative, not exhaustive.
DAGassist
is model-agnostic: if an engine accepts a
standard formula + data
interface, it will usually
work.
If you want support documented (or added) for an engine not shown here, please open an issue or PR on GitHub.
Package | Function |
---|---|
estimatr | lm_robust |
fixest | feglm |
fixest | feols |
lfe | felm |
lme4 | glmer |
lmerTest | lmer |
MASS | glm.nb |
stats | lm |
clusters = cat_b
, "cat_b"
, or
~cat_b
). DAGassist
resolves them within
data
.(1 | group)
) and fixest FE/IV tails (| fe ...)
in your formula are preserved.DAGassist
breaks if the exposure is missing or mismatched.DAGassist(
dag = dag_model,
formula = estimatr::lm_robust(
ancvs_change_1116 ~ western_belt +
unemploy_broad + black_popshare + col_popshare +
indasian_popshare + other_popshare + share_formal +
share_informal + share_traditional + afrikaans_popshare +
english_popshare + isindebele_popshare + isixhosa_popshare +
sepedi_popshare + sesotho_popshare + setswana_popshare +
signlanguage_popshare + siswati_popshare + tshivenda_popshare +
xitsonga_popshare +
latitude + longitude + latitudelongitude,
data = df,
clusters = cat_b)
)
DAGassist(
dag = dag_model2,
formula = fixest::feglm(
exc_eq ~ cat4_prevalence_best + nonvprotgovt + v2x_gencs +
WINGOImputed_fill + UNintervention + majpowintervention + UNwomen +
religious + ideolleft + lgt + substantive + v2x_gencl +
Krause_wpm_neg + eqgen_binary,
data = df %>% filter(interstateonly==0, inter_intrastate==0),
family = binomial("logit"),
cluster = ~cowcode
)
)
DAGassist(dag=dag_model,
formula = lfe::felm(
share_female ~ lag_democracy_stock_poly_95 + lag_v2xcl_rol +
lag_v2xcl_prpty + lag_v2x_rule + lag_v2x_jucon +
lag_v2xlg_legcon + lag_v2x_corr + lag_v2clstown +
lag_v2xcs_ccsi + lag_v2xps_party | year + country_isocode | 0 |
country_isocode,
data=df_cross)
)
DAGassist(
dag = dag_model,
formula = lme4::glmer(
dsu_file ~ specific + lnearnings + distortion + progress + duration +
eu + japan + mexico + korea + nonoecd +
lntotdirx + lnprod + lnpolcon + active301 +
(1 | isic3_4dig),
data = df,
family = binomial(link = "logit"),
control = glmerControl(optimizer = "bobyqa"))
)
DAGassist(
dag = dag_model,
formula = MASS::glm.nb(
protestcount ~ civilcas_percapita + sigact_percapita + log_pop + shiapop_perc
kurdpop_perc + urban + totaloilvolx + lognearestcity + feb2011 + nov2010 +
laggedprotestcount + illiterate + incomequintilelowest +
incomequintilehighest + urate + powercontinuous,
data = iraqevents_timeseries_small,
control = glm.control(maxit = 50),
link = "log")
)
DAGassist(
dag = dag_model,
formula = stats::lm(
restraint ~ nonvio2 + prime_frat + prime_future + prime_RU + prime_UN +
oppose92coup2 + civwar + islamist + supp_sharia + active + conscript +
soldier + junoff + senoff + branch2 + train_west + train_russia +
train_china + young + sex + edu + urban_area + employed + student +
arabic + econ1 + corr1 + dem + supp_opp_parties + continue + protested +
preboutef + post_exp + mon + factor(fgov),
data=data)
)
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.