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Regne eksempel på SEXRAT i datasæt
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@enerammer
enerammer authored Nov 13, 2024
2 parents eaa8a69 + 84067ae commit 711443a
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4 changes: 2 additions & 2 deletions config.yaml
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Expand Up @@ -23,8 +23,8 @@ keywords: 'software, data, lesson'
# possible values: pre-alpha, alpha, beta, stable
life_cycle: 'pre-alpha'

# License of the lesson materials (recommended CC-BY 4.0)
license: 'CC-BY 4.0'
# License of the lesson materials (recommended: CC BY-NC-SA 4.0)
license: 'CC0'

# Link to the source repository for this lesson
source: 'https://github.com/KUBDatalab/R-toolbox'
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142 changes: 111 additions & 31 deletions learners/data.md
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Expand Up @@ -31,7 +31,7 @@ and took 1 pill every other day for 12 weeks. Blood samples were drawn after

_Dimensions:_ Rows: 23 Columns: 8

[source](data.md#rosner_1)^1^
[Source](data.md#rosner_1)^1^

[Download](https://raw.githubusercontent.com/KUBDatalab/R-toolbox/main/episodes/data/BETACAR.csv)

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[source](data.md#rosner_1)^1^
[Source](data.md#rosner_1)^1^

[Download](https://raw.githubusercontent.com/KUBDatalab/R-toolbox/main/episodes/data/BLOOD.csv)

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[source](data.md#rosner_1)^1^
[Source](data.md#rosner_1)^1^

[Download](https://raw.githubusercontent.com/KUBDatalab/R-toolbox/main/episodes/data/BONEDEN.csv)

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[source](data.md#rosner_1)^1^
[Source](data.md#rosner_1)^1^

[Download](https://raw.githubusercontent.com/KUBDatalab/R-toolbox/main/episodes/data/BOTOX.csv)

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[source](data.md#rosner_1)^1^
[Source](data.md#rosner_1)^1^

[Download](https://raw.githubusercontent.com/KUBDatalab/R-toolbox/main/episodes/data/CORNEAL.csv)

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[source](data.md#rosner_1)^1^
[Source](data.md#rosner_1)^1^

[Download](https://raw.githubusercontent.com/KUBDatalab/R-toolbox/main/episodes/data/DIABETES.csv)

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[source](data.md#rosner_1)^1^
[Source](data.md#rosner_1)^1^

[Download](https://raw.githubusercontent.com/KUBDatalab/R-toolbox/main/episodes/data/FIELD.csv)

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[source](data.md#rosner_1)^1^
[Source](data.md#rosner_1)^1^

[Download](https://raw.githubusercontent.com/KUBDatalab/R-toolbox/main/episodes/data/HOSPITAL.csv)

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[source](data.md#rosner_1)^1^
[Source](data.md#rosner_1)^1^

[Download](https://raw.githubusercontent.com/KUBDatalab/R-toolbox/main/episodes/data/INFANTBP.csv)

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[source](data.md#rosner_1)^1^
[Source](data.md#rosner_1)^1^

[Download](https://raw.githubusercontent.com/KUBDatalab/R-toolbox/main/episodes/data/LEAD.csv)

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[source](data.md#rosner_1)^1^
[Source](data.md#rosner_1)^1^

[Download](https://raw.githubusercontent.com/KUBDatalab/R-toolbox/main/episodes/data/MICE.csv)

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[source](data.md#rosner_1)^1^
[Source](data.md#rosner_1)^1^

[Download](https://raw.githubusercontent.com/KUBDatalab/R-toolbox/main/episodes/data/NEPHRO.csv)

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_Dimensions:_ Rows: 34 Columns: 10

[source](data.md#rosner_1)^1^
[Source](data.md#rosner_1)^1^

[Download](https://raw.githubusercontent.com/KUBDatalab/R-toolbox/main/episodes/data/NIFED.csv)

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[source](data.md#rosner_1)^1^
[Source](data.md#rosner_1)^1^

[Download](https://raw.githubusercontent.com/KUBDatalab/R-toolbox/main/episodes/data/OTO.csv)

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_Dimensions:_ Rows: 631 Columns: 5

[source](data.md#rosner_1)^1^
[Source](data.md#rosner_1)^1^

[Download](https://raw.githubusercontent.com/KUBDatalab/R-toolbox/main/episodes/data/PIRIFORM.csv)

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### SEXRAT

Frequencies of different sex orders of the first 5 children born in families.

Does the probability of a male birth differ from 50%?

Are the sex distribution of successive offspring independent? Ie, does the
sex of the first born child, affect the probability of the second child?


_Dimensions:_ Rows: 60 Columns: 8

[source](data.md#rosner_1)^1^
[Source](data.md#rosner_1)^1^

[Download](https://raw.githubusercontent.com/KUBDatalab/R-toolbox/main/episodes/data/SEXRAT.csv)

Expand All @@ -1043,8 +1051,6 @@ _Dimensions:_ Rows: 60 Columns: 8
| sexchldn* | Sex of all children |
| num_fam** | Number of families |

::::

+ For families with 5+ children, the sex of the first 5 children are listed.
The number of children is given as 5 for such families.

Expand All @@ -1054,12 +1060,84 @@ such families.

** Number of families with specific gender contribution of children

Example; there are:

* 4400 families with 2 children where both children are male,
* 4270 families with 2 children where the first child is male, and the second female and,
* 4633 families with 2 children where the first child is female and the second male.

::::


:::: spoiler

## Example

Compare P(child 2 is male | child 1 is female) with P(child 2 is male | child 1 is male)

That is, the probability child 2 is male given that child 1 is female.

```r
sexrat <- read_csv("https://raw.githubusercontent.com/KUBDatalab/R-toolbox/main/episodes/data/SEXRAT.csv")

# Number of families with female first child:

sexrat %>%
filter(sx_1 == "F") %>%
summarise(nF1 = sum(num_fam))

# A tibble: 1 x 1
nF1
<dbl>
1 25719

# Number of those families with a male second child:

sexrat %>%
filter(sx_1 == "F",
sx_2 == "M") %>%
summarise(nF1M2 = sum(num_fam))

# A tibble: 1 x 1
nF1M2
<dbl>
1 12882

# Point estimate for probability of child 2 being male, given child 1 is female:

pF1M2 <- 12882/25719
pF1M2

[1] 0.5008748

# Standard error of mean for proportions:

SEM_F1M2 <- sqrt(pF1M2*(1-pF1M2)/25719)
SEM_F1M2
[1] 0.003117757

# That gives us a 95% confidence interval for P(Child 2 is male | Child 1 is female):

pF1M2 + c(-1,1)*1.96*SEM_F1M2

[1] 0.4947640 0.5069856
# Doing the same calculations for P(Child 2 is male | Child 1 is male)
# gives us an interval of (rounded):

[1] 0.512 0.524

# Which would indicate the having a male child first, increases the probability
# of having a second male child.
```

::::


### SMOKE

_Dimensions:_ Rows: 234 Columns: 8

[source](data.md#rosner_1)^1^
[Source](data.md#rosner_1)^1^

[Download](https://raw.githubusercontent.com/KUBDatalab/R-toolbox/main/episodes/data/SMOKE.csv)

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[source](data.md#rosner_1)^1^
[Source](data.md#rosner_1)^1^

[Download](https://raw.githubusercontent.com/KUBDatalab/R-toolbox/main/episodes/data/SWISS.csv)

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[source](data.md#rosner_1)^1^
[Source](data.md#rosner_1)^1^

[Download](https://raw.githubusercontent.com/KUBDatalab/R-toolbox/main/episodes/data/TEAR.csv)

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_Dimensions:_ Rows: 630 Columns: 6

[source](data.md#rosner_1)^1^
[Source](data.md#rosner_1)^1^

[Download](https://raw.githubusercontent.com/KUBDatalab/R-toolbox/main/episodes/data/TEMPERAT.csv)

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_Dimensions:_ Rows: 444 Columns: 12

[source](data.md#rosner_1)^1^
[Source](data.md#rosner_1)^1^

[Download](https://raw.githubusercontent.com/KUBDatalab/R-toolbox/main/episodes/data/TENNIS1.csv)

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_Dimensions:_ Rows: 88 Columns: 16

[source](data.md#rosner_1)^1^
[Source](data.md#rosner_1)^1^

[Download](https://raw.githubusercontent.com/KUBDatalab/R-toolbox/main/episodes/data/TENNIS2.csv)

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_Dimensions:_ Rows: 173 Columns: 9

[source](data.md#rosner_1)^1^
[Source](data.md#rosner_1)^1^

[Download](https://raw.githubusercontent.com/KUBDatalab/R-toolbox/main/episodes/data/VALID.csv)

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Også Rosner...

[source](learners/data.md#jorgensen_4)^4^
[Source](learners/data.md#jorgensen_4)^4^

[Download](https://raw.githubusercontent.com/KUBDatalab/R-toolbox/main/episodes/data/spermatozoa.csv)

Expand All @@ -1448,6 +1526,8 @@ Også Rosner...

_Dimensions:_ Rows: 405440 Columns: 10

[Source](learners/data.md#jorgensen_4)^4^ and [Source](learners/data.md#who_7)^7^

[Download](https://raw.githubusercontent.com/KUBDatalab/R-toolbox/main/episodes/data/who.csv)

NB: Filen er semikolon-separeret
Expand Down Expand Up @@ -1481,10 +1561,7 @@ NB: Filen er semikolon-separeret
## References


Bortset fra who-sættet, der er en modificeret udgave af datasættet who fra
tidyr-pakken.

Den oprindelige kilde til det datasæt: https://www.who.int/teams/global-tuberculosis-programme/data



Expand All @@ -1507,6 +1584,10 @@ Den oprindelige kilde til det datasæt: https://www.who.int/teams/global-tubercu

<a id="rosner_1">1</a>: Rosner, Bernard A. Fundamentals of Biostatistics, 7/e, International Edition, 2011 ISBN: 9780538735896. https://www.cengage.com/cgi-wadsworth/course_products_wp.pl?fid=M20b&product_isbn_issn=9780538733496&token

der er også guf her https://www.doc88.com/p-5925003681540.html

https://statanaly.com/wp-content/uploads/2023/04/Fundamentals-of-Biostatistics-7th-Edition.pdf

<a id="hopper_2">2</a>: Hopper, J.H. & Seeman, E (1994). The bone density
of female twins discordant for tobacco use. New England Journal of Medicine, 330, 387-392.

Expand All @@ -1524,7 +1605,7 @@ https://www.jstor.org/stable/2532505

<a id ="tage_6">6</a>: Tage, I.B., Weiss, S.T., Rosner, B. & Speizer, F.E. (1979), Effect of parental cigarette smoking on pulmonary function in children. American Journal of Epidemiology, 110, 15-26.


<a id = "who_7">7</a>: https://www.who.int/teams/global-tuberculosis-programme/data


## listen over datasæt.
Expand All @@ -1540,7 +1621,6 @@ Der hakkes af efterhånden som de er færdige - og så er issue 113 done.
* nifed
* oto
* piriform
* sexrat
* smoke
* tear
* temperat
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