**sampsi** continues to work but, as of Stata 13, is no longer an official
part of Stata. This is the original help file, which we will no longer
update, so some links may no longer work.

See **[PSS] power** for a recommended alternative to **sampsi**.

__Title__

**[R] sampsi** -- Sample size and power for means and proportions

__Syntax__

**sampsi** *#1 #2* [**,** *options*]

*options* Description
-------------------------------------------------------------------------
Main
__onesam__**ple** one-sample test; default is two-sample
**sd1(***#***)** standard deviation of sample 1
**sd2(***#***)** standard deviation of sample 2

Options
__a__**lpha(***#***)** significance level of test; default is **alpha(0.05)**
__p__**ower(***#***)** power of test; default is **power(0.90)**
__n__**1(***#***)** size of sample 1
__n__**2(***#***)** size of sample 2
__r__**atio(***#***)** ratio of sample sizes; default is **ratio(1)**
**pre(***#***)** number of baseline measurements; default is **pre(0)**
**post(***#***)** number of follow-up measurements; default is **post(1)**
__nocont__**inuity** do not use continuity correction for two-sample test
on proportions
**r0(***#***)** correlation between baseline measurements; default is
**r0()=r1()**
**r1(***#***)** correlation between follow-up measurements
**r01(***#***)** correlation between baseline and follow-up
measurements
__onesid__**ed** one-sided test; default is two-sided
__m__**ethod(***method***)** analysis method where *method* is **post**, **change**, **ancova**,
or **all**; default is **method(all)**
-------------------------------------------------------------------------

__Menu__

__sampsi__

**Statistics > Power and sample size > Tests of means and proportions**

__sampsi with repeated measures__

**Statistics > Power and sample size > Tests of means with repeated**
**measures**

__Description__

**sampsi** estimates require sample size or power of tests for studies
comparing two groups. **sampsi** can be used when comparing means or
proportions for simple studies where only one measurement of the outcome
is planned and for comparing mean summary statistics for more complex
studies where repeated measurements of the outcome on each experimental
unit are planned.

If **n1(***#***)** or **n2(***#***)** is specified, **sampsi** computes power; otherwise, it
computes sample size. For simple studies, if **sd1(***#***)** or **sd2(***#***)** is
specified, **sampsi** assumes a comparison of means; otherwise, it assumes a
comparison of proportions. For repeated measurements, **sd1(***#***)**, or **sd2(***#***)**
must be specified. **sampsi** is an immediate command; all its arguments are
numbers; see immed.

For simple studies, where only one measurement of the outcome is planned,
**sampsi** computes sample size or power for four types of tests:

1. Two-sample comparison of means.
The postulated values of the means are *#1* and *#2*.
The postulated standard deviations are **sd1()** and **sd2()**.

2. One-sample comparison of mean with hypothesized value.
Option **onesample** must be specified.
The hypothesized value (null hypothesis) is *#1*.
The postulated mean (alternative hypothesis) is *#2*.
The postulated standard deviation is **sd1()**.

3. Two-sample comparison of proportions.
The postulated values of the proportions are *#1* and *#2*.

4. One-sample comparison of proportion with hypothesized value.
Option **onesample** must be specified.
The hypothesized proportion (null hypothesis) is *#1*.
The postulated proportion (alternative hypothesis) is *#2*.

__Options__

+------+
----+ Main +-------------------------------------------------------------

**onesample** indicates a one-sample test. The default is two-sample.

**sd1(***#***)** and **sd2(***#***)** are the standard deviations of population 1 and
population 2, respectively. One or both must be specified when doing
a comparison of means. When the **onesample** option is used, **sd1(***#***)** is
the standard deviation of the single sample (it can be abbreviated as
**sd(***#***)**). If only one of **sd1(***#***)** or **sd2(***#***)** is specified, **sampsi** assumes
that **sd1()** = **sd2()**. If neither **sd1(***#***)** nor **sd2(***#***)** is specified,
**sampsi** assumes a test of proportions. For repeated measurements,
**sd1(***#***)** or **sd2(***#***)** must be specified.

+---------+
----+ Options +----------------------------------------------------------

**alpha(***#***)** is the significance level of the test. The default is
**alpha(0.05)** unless **set level** has been used to reset the default
significance level for confidence intervals. If a **set level** #-level
command has been issued, the default value is **alpha(**1-level/100**)**.
See **[R] level**.

**power(***#***)** = 1 - b is the power of the test. The default is **power(0.90)**.

**n1(***#***)** and **n2(***#***)** are the sizes of sample 1 and sample 2, respectively.
One or both must be specified when computing power. If neither **n1(***#***)**
nor **n2(***#***)** is specified, **sampsi** computes sample size. When the
**onesample** option is used, **n1(***#***)** is the size of the single sample (it
can be abbreviated as **n(***#***)**). If only one of **n1(***#***)** or **n2(***#***)** is
specified, the unspecified one is computed using the formula **ratio** =
**n2()**/**n1()**.

**ratio(***#***)** is the ratio of sample sizes for two-sample tests: **ratio()** =
**n2()**/**n1()**. The default is **ratio(1)**.

**pre(***#***)** specifies the number of baseline measurements (prerandomization)
planned in a repeated-measure study. The default is **pre(0)**.

**post(***#***)** specifies the number of follow-up measurements
(postrandomization) planned in a repeated-measure study. The default
is **post(1)**.

**nocontinuity** requests power and sample size calculations without
continuity correction for two-sample test on proportions. If not
specified, the continuity correction is used.

**r0(***#***)** specifies the correlation between baseline measurements in a
repeated-measure study. If **r0(***#***)** is not specified, **sampsi** assumes
that **r0()** = **r1()**.

**r1(***#***)** specifies the correlation between follow-up measurements in a
repeated-measure study. For a repeated-measure study, either **r1(***#***)**
or **r01(***#***)** must be specified. If **r1(***#***)** is not specified, **sampsi**
assumes that **r1()** = **r01()**.

**r01(***#***)** specifies the correlation between baseline and follow-up
measurements in a repeated-measure study. For a repeated-measure
study, either **r01(***#***)** or **r1(***#***)** must be specified. If **r01(***#***)** is not
specified, **sampsi** assumes that **r01()** = **r1()**.

**onesided** indicates a one-sided test. The default is two-sided.

**method(post**|**change**|**ancova**|**all)** specifies the analysis method to be used
with repeated measures. **change** and **ancova** can be used only if
baseline measurements are planned. The default is **method(all)**, which
means to use all three methods.

__Examples__

1. Two-sample comparison of mean1 to mean2. Compute sample sizes with
n2/n1 = 2:

**. sampsi 132.86 127.44, p(0.8) r(2) sd1(15.34) sd2(18.23)**

Compute power with n1 = n2, sd1 = sd2, and alpha = 0.01 one-sided:

**. sampsi 5.6 6.1, n1(100) sd1(1.5) a(0.01) onesided**

2. One-sample comparison of mean to hypothesized value = 180. Compute
sample size:

**. sampsi 180 211, sd(46) onesam**

One-sample comparison of mean to hypothesized value = 0. Compute
power:

**. sampsi 0 -2.5, sd(4) n(25) onesam**

3. Two-sample comparison of proportions. Compute sample size with n1 =
n2 (that is, ratio = 1, the default) and power = 0.9 (the default):

**. sampsi 0.25 0.4**

Compute power with n1 = 500 and ratio = n2/n1 = 0.5:

**. sampsi 0.25 0.4, n1(300) r(0.5)**

4. One-sample comparison of proportion to hypothesized value = 0.5:

**. sampsi 0.5 0.75, power(0.8) onesample**

Compute power:

**. sampsi 0.5 0.6, n(200) onesam**

5. Repeated measures:

**. sampsi 498 485, sd1(20.2) sd2(19.5) method(change) pre(1) post(3)**
**r1(.7)**

Compute power:

**. sampsi 498 485, sd1(20.2) sd2(19.5) method(change) pre(1) post(3)**
**r1(.7) n1(15) n2(15)**

__Stored results__

**sampsi** stores the following in **r()**:

Scalars
**r(N_1)** sample size n_1
**r(N_2)** sample size n_2
**r(power)** power
**r(adj)** adjustment to the SE
**r(warning)** 0 if assumptions are satisfied and 1 otherwise