Cite a table cell in inline text

Returns one cell of a spicy table as a character scalar, formatted exactly as the table displays it – same decimals, same p style, same interval punctuation, same journal style. Designed for inline R chunks in Quarto / R Markdown:

Smokers had higher odds (`r inline(tbl, smoking, "Yes", "or")`).

Usage

inline(x, variable, level = NULL, column = NULL, model = NULL)

Arguments

x: A table returned by table_regression(), table_categorical(), table_continuous(), table_continuous_lm(), table_outcome(), table_categorical_svy() or table_continuous_svy() (default output) – every family as_structured() accepts.
variable: The source variable, unquoted or as a string; or a fit-statistic token ("n", "r2", ...).
level: For a factor variable, the level, as a string. "(Missing)" addresses the missing-value category by role. On table_continuous_lm(), whose groups are columns rather than rows, it names the group.
column: A column token, or a {token} pattern. NULL (the default) returns the estimate-like column of the row when it is unambiguous: the family's primary estimate. That is the coefficient for table_regression() – always token "b": an exponentiated table changes its header to OR, IRR or HR, never its token – the contrast ("delta") or, across a numeric by, the slope ("b") for table_continuous_lm(), the mean ("m") or, on a median-only table, the median ("med", "med_iqr") for table_continuous(), and the count ("n") for table_categorical(). A row carrying none of them refuses and lists its tokens.
model: In a multi-model table, the model: its label (as displayed in the column spanners) or its position.

Value

A character scalar.

Addressing

The row is found by identity, not by display text: variable names the source column (.variable in the typed body), level the level (.level). Custom labels, a style, or a translated display never change the call. As a convenience, a variable that matches no source column is looked up among the displayed labels before erroring. The missing-value category is addressed by level = "(Missing)" whatever its displayed (possibly deduplicated) label, through its row role. Fit statistics are addressed by their token as variable (inline(tbl, "n"), inline(tbl, "r2")).

A statistic that belongs to a whole variable rather than to one of its levels sits on the variable's own row: the p of a table_categorical() block, its association measure, its SMD. Leave level out to cite it (inline(tbl, smoking, column = "p")).

table_continuous_lm() lays its groups out sideways – one row per outcome, the by levels as columns (M (Female), M (Male)) – so there level names the group whose column you want: inline(tbl, bmi, "Female", "emmean"). The columns that belong to no group (the contrast, its interval, p, n) are cited without one, as before.

The column is a token of the typed contract ("b", "se", "p", "ci", "or", "ame", "n", "pct", "m", ... – see as_structured()'s col_meta), never a display header. "ci" composes the interval with the style's brackets and separator, and so does every other interval token the table carries ("med_ci", "ame_ci", "assoc_ci"): each addresses its own bounds. In a multi-model table, model selects the model by its spanner label or position; in a by table, the spanners are the groups, so model selects the group the same way.

Patterns

A column containing { is a pattern: each {token} is replaced by the corresponding cell, so one call quotes a full sentence fragment:

inline(tbl, smoking, "Yes", "{or} ({ci_label} {ci}; p = {p})")

{ci_label} inserts the interval label of the interval the pattern cites (95% CI, or Med 95% CI in a pattern quoting {med_ci}) – the first one when it cites several, the table's first when it cites none. Note that {p} carries the floor operator when the table does (<.001), so write p {p} rather than p = {p} in patterns that may hit the floor.

Errors

Every misaddressing is a classed error that lists the available choices: unknown variables list the variables, missing levels list the levels, unknown tokens list the table's tokens, ambiguous models list the spanner labels. A cell the table itself displays as undefined (an aliased coefficient's en-dash) refuses with the reason rather than pasting a dash into a sentence.

Examples

fit <- lm(wellbeing_score ~ age + sex, data = sochealth)
tbl <- table_regression(fit)
inline(tbl, age, column = "b")
#> [1] "0.04"
inline(tbl, sex, "Male", "{b} ({ci_label} {ci}; p {p})")
#> [1] "3.90 (95% CI [2.14, 5.65]; p <.001)"
inline(tbl, "n")
#> [1] "1200"