analyze_fixef_plot

source

analyze_fixef_plot(result_or_model, *, fixef=None, top_n=30, title=None)

Plot the estimated group intercepts (fixed effects) of a model, ranked by value.

Parameters

Name	Type	Description	Default
result_or_model	Any	A fitted model or a result object carrying .models.	required
fixef	str | None	Which fixed-effect dimension to plot (e.g. "country"). Defaults to the first.	None
top_n	int | None	Show at most this many levels; when there are more, the most extreme (lowest and highest) are kept. None shows every level.	30
title	str | None	Optional figure title.	None

Returns

Name	Type	Description
	FixefPlotResult	df (fixef, level, value) and the Plotly figure.

Examples

Basic — plot the country fixed effects of a Kuznets-curve model:

import expdpy as ex
from expdpy.data import load_kuznets, load_kuznets_data_def

df = ex.set_labels(load_kuznets(), load_kuznets_data_def(), set_panel=True)
model = ex.analyze_regression_table(
    df,
    dvs="gini_regional",
    idvs=["log_gdp_pc", "log_gdp_pc_sq", "log_gdp_pc_cu"],
    feffects=["country"],
)
ex.analyze_fixef_plot(model).fig

Advanced — show only the most extreme levels with a custom title:

import expdpy as ex
from expdpy.data import load_kuznets, load_kuznets_data_def

df = ex.set_labels(load_kuznets(), load_kuznets_data_def(), set_panel=True)
model = ex.analyze_regression_table(
    df,
    dvs="gini_regional",
    idvs=["log_gdp_pc", "log_gdp_pc_sq", "log_gdp_pc_cu"],
    feffects=["country"],
)
ex.analyze_fixef_plot(
    model, fixef="country", top_n=10, title="Country intercepts"
).fig